Quickest Change Detection with Confusing Change
In Proc. Asilomar 2024, July 2024 (Accepted)
Yu-Zhen (Janice) Chen, Jinhang Zuo, Venu Veeravalli, Don Towsley
Adaptive Step-size Procedures for Compressed SGD
IEEE Transactions on Signal Processing, April 2024 (Accepted)
Adarsh Subramaniam, Akshayaa Magesh, Venu Veeravalli
Distributed and Rate-Adaptive Feature Compression
arxiv preprint, April 2024
Aditya Deshmukh, Gunjan Verma, Venu Veeravalli
CACTUS: Dynamically Switchable Context-aware micro-Classifiers for Efficient IoT Inference
In Proc. 22nd ACM International Conference on Mobile Systems, Applications, and Services (ACM MobiSys 2024), April 2024 (Accepted)
Deepak Ganesan
A Framework for Time-Varying Optimization via Derivative Estimation
In Proc. European Control Conference, March 2024 (Accepted)
Matteo Marchi, Jonathan Bunton, Joao Pedro Silvestre
A Framework for Time-Varying Optimization via Derivative Estimation
In Proc. European Control Conference, March 2024 (Accepted)
Matteo Marchi, Jonathan Bunton, Joao Pedro Silvestre, Paulo Tabuada
Comparing Task Graph Scheduling Algorithms: An Adversarial Approach
arXiv preprint arXiv:2403.07120 (https://arxiv.org/abs/2403.07120), March 2024
Jared Coleman, Bhaskar Krishnamachari
Parameterized Task Graph Scheduling Algorithm for Comparing Algorithmic Components
arXiv preprint (https://arxiv.org/pdf/2403.07112) , March 2024
Jared Coleman, Ravi Vivek Agrawal, Ebrahim Hirani, Bhaskar Krishnamachari
Distributionally Robust Quickest Change Detection using Wasserstein Uncertainty Sets
In Proc. Proc. 27th International Conference on Artificial Intelligence and Statis- tics (AISTATS), Valencia, Spain, May 2024, February 2024 (Accepted)
Venu Veeravalli, Yuchen Liang
Quickest Change Detection with Controlled Sensing
IEEE Journal on Selected Areas in Information Theory, February 2024
Venu Veeravalli
Counterexample Guided Inductive Synthesis Using Large Language Models and Satisfiability Solving
In Proc. MILCOM 2023, December 2023
Susmit Jha, Nathaniel Bastian
Neural SDEs for Robust and Explainable Analysis of Electromagnetic Unintended Radiated Emissions
In Proc. MILCOM 2023, December 2023
Susmit Jha
Challenges and Opportunities in Neuro-Symbolic Composition of Foundation Models
In Proc. MILCOM IoT Workshop 2023, December 2023
Susmit Jha, Nathaniel Bastian
Trinity - Assured Neuro-symbolic Model Inspired by Hierarchical Predictive Coding
In Proc. DAC'23, December 2023
Susmit Jha
Model-driven Cluster Resource Management for AI Workloads in Edge Clouds
ACM Transactions on Adaptive andAutonomous Systems (TAAS), 2023, December 2023 (Accepted)
Qianlin Liang, Walid Hanafy, Ahmed Ali-Eldin, Prashant Shenoy
SODA: Protecting Proprietary Information in On-Device Machine Learning Models
In Proc. Proceedings of the 8th ACM/IEEE Symposium on Edge Computing, 2023, December 2023
Akanksha Atrey, Ritwik Sinha, Saayan Mitra, Prashant Shenoy
Principled Out-of-Distribution Detection via Multiple Testing
Journal of Machine Learning Research, November 2023
Susmit Jha, Venu Veeravalli, Anirban Roy, Akshayaa Magesh
DDPC: Automated Data-Driven Power-Performance Controller Design on-the-fly for Latency-sensitive Web Services
In Proc. Proceedings of the Web Conference, Austin, TX, 2023, November 2023
Mehmet Savasci, Ahmed Ali-Eldin, Johan Eker, Anders Robertsson, Prashant Shenoy
Efficient Batched Algorithm for Contextual Linear Bandits with Large Action Space via Soft Elimination
In Proc. Neurips 2023, November 2023 (Accepted)
Osama Hanna, Lin Yang, Christina Fragouli
Online Allocation of Sensing and Computation in Large Graphs
In Proc. 2023 IEEE International Conference on Collaboration and Internet Computing, November 2023
Xinlin Li, Merve Karakas, Osama Hanna, Merhrad Kiamari, Jared Coleman, Christina Fragouli, Bhaskar Krishnamachari, Gunjan Verma
Unlocking Efficiency: Understanding End-to-End Performance in Distributed Analytics Pipelines
In Proc. Proceedings of the 41st IEEE Military Communications Conference (MILCOM) workshop on Internet of Things for Adversarial Environments Oct 2023, November 2023
Prashant Shenoy, Tarek Abdelzaher, Don Towsley, Abel Souza, Nathan Ng
Failure-Resilient ML Inference at the Edge through Graceful Service Degradation
In Proc. Proceedings of the 41st IEEE Military Communications Conference (MILCOM) workshop on Internet of Things for Adversarial Environments Oct 2023, November 2023
Prashant Shenoy, Suhas Diggavi, Tarek Abdelzaher, Walid Hanafy, Li Wu
TIJO: Trigger Inversion with Joint Optimization for Defending Multimodal Backdoored Models
In Proc. ICCV 2023, September 2023
Susmit Jha
CODiT: Conformal Out-of-Distribution Detection in Time-Series Data for Cyber-Physical Systems
In Proc. ICCPS'23 (best paper nomination), September 2023
Susmit Jha
Detecting Trojaned DNNs Using Counterfactual Attributions
In Proc. ICAA'23, September 2023
Susmit Jha
Predicting Out-of-Distribution Performance of Deep Neural Networks Using Model Conformance
In Proc. ICAA'23, September 2023
Susmit Jha
Contexts can be Cheap: Solving Stochastic Contextual Bandits with Linear Bandit Algorithms
In Proc. COLT, September 2023
Osama Hanna, Lin Yang, Christina Fragouli
Multi-Arm Bandits over Action Erasure Channels
In Proc. ISIT, September 2023
Osama Hanna, Merve Karakas, Lin Yang, Christina Fragouli
Decentralized Multi-Task Stochastic Optimization and Compressed Communications
Automatica, August 2023 (Accepted)
Navjot Singh, Xuanyu Cao, Suhas Diggavi, Tamer Basar
Byzantine-Resilient High-Dimensional SGD with Local Iterations on Heterogeneous Data
IEEE Transactions on Information Theory, August 2023 (Accepted)
Deepesh Data, Suhas Diggavi
Heteroskedastic Geospatial Tracking with Distributed Camera Networks
In Proc. Conference on Uncertainty in Artificial Intelligence, July 2023
Colin Samplawski, Shiwei Fang, Ziqi Wang, Deepak Ganesan , Mani Srivastava, Ben Marlin
TwinSync: A Digital Twin Synchronization Protocol for Bandwidth-limited IoT Applications
In Proc. IEEE ICCCN , July 2023
Deepti Kalasapura, Jinyang Li, Shengzhong Liu, Yizhuo Chen, Ruijie Wang, Tarek Abdelzaher, Matt Caesar, Joydeep Bhattacharyya, Jae Kim, Guijun Wang, Greg Kimberly, Josh Eckhardt, Denis Osipychev
Underprovisioned GPUs: On Sufficient Capacity for Real-Time Mission-Critical Perception
In Proc. IEEE ICCCN , July 2023
Yigong Hu, Ila Gokarn, Shengzhong Liu, Archan Misra, Tarek Abdelzaher
Representation Transfer Learning via Multiple Pre-Trained Models for Linear Regression
In Proc. IEEE International Symposium on Information Theory, July 2023Personalized PCA for Federated Heterogeneous Data
In Proc. IEEE International Symposium on Information Theory, July 2023
Kaan Ozkara, Bruce Huang, Suhas Diggavi
Common Information Dimension
In Proc. IEEE International Symposium on Information Theory, July 2023
Osama Hanna, Xinlin Li, Suhas Diggavi, Christina Fragouli
Deep VULMAN: A Deep Reinforcement Learning-enabled Cyber Vulnerability Management Framework
Expert Systems with Applications, July 2023
Soumyadeep Hore, Ankit Shah, Nathaniel Bastian
Challenges in Metaverse Research: An Internet of Things Perspective
In Proc. IEEE MetaCom, June 2023
Tarek Abdelzaher, Matt Caesar, Charith Mendis, Klara Nahrstedt, Mani Srivastava, Minlan Yu
Depth Estimation from Camera Image and mmWave Radar Point Cloud
In Proc. The 2023 IEEE / CVF Computer Vision and Pattern Recognition Conference (CVPR 2023), June 2023
Akash Deep Singh, Yunhao Ba, Ankur Sarker, Howard Zhang, Achuta Kadambi, Stefano Soatto, Mani Srivastava, Alex Wong
Generalized Self-Cueing Real-Time Attention Scheduling with Intermittent Inspection and Image Resizing
Journal of Real-time Systems, June 2023 (Accepted)
Shengzhong Liu, Xinzhe Fu, Yigong Hu, Maggie Wigness, Philip David, Shuochao Yao, Lui Sha, Tarek Abdelzaher
Data-Efficient, Federated Learning for Raw Network Traffic Detection
In Proc. Proceedings of the 2023 SPIE Conference on Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications V, June 2023
Mikal Willeke, David Bierbrauer, Nathaniel Bastian
Graph Representation Learning for Context-Aware Network Intrusion Detection
In Proc. Proceedings of the 2023 SPIE Conference on Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications V, June 2023
Augustine Premkumar, Madeleine Schneider, Carlton Spivey, John Pavlik, Nathaniel Bastian
MOSAIC: Spatially-Multiplexed Edge AI Optimization over Multiple Concurrent Video Sensing Streams
In Proc. ACM MMSYS, June 2023
Ila Gokarn, Hemanth Sabbella, Yigong Hu, Tarek Abdelzaher, Archan Misra
Dehallucinating Large Language Models Using Formal Methods Guided Iterative Prompting
In Proc. Proceedings of the 2023 2023 IEEE International Conference on Assured Autonomy, June 2023
Susmit Jha, Sumit Jha, Patrick Lincoln, Nathaniel Bastian, Alvaro Velasquez, Sandeep Neem
Novelty Detection in Network Traffic: Using Survival Analysis for Feature Identification
In Proc. Proceedings of the 2023 IEEE International Conference on Assured Autonomy, June 2023
Taylor Bradley, Elie Alhajjar, Nathaniel Bastian
Explainable Learning-Based Intrusion Detection Supported by Memristors
In Proc. Proceedings of the 2023 IEEE Conference on Artificial Intelligence, June 2023
Jingdi Chen, Lei Zhang, Joseph Riem, Gina Adam, Nathaniel Bastian, Tian Lan
TinyNS: Platform-Aware Neurosymbolic Auto Tiny Machine Learning
ACM Transactions on Embedded Computing Systems, May 2023
Swapnil Saha, Sandeep Singh Sandha, Mohot Aggarwal, Brian Wang, Liying Han, Julia de Gortari Briseno, Mani Srivastava
Neural-Kalman GNSS/INS Navigation for Precision Agriculture
In Proc. 2023 IEEE International Conference on Robotics and Automation (ICRA) , May 2023
Yayun Du, Swapnil Saha, Sandeep Singh Sandha, Arthur Lovekin, Jason Wu, S. Siddharth, Mahesh Chowdhary, Mohammad Khalid Jawed, Mani Srivastava
Constrained Optimization Based Adversarial Example Generation for Transfer Attacks in Network Intrusion Detection Systems
Optimization Letters, May 2023
Marc Chale, Bruce Cox, Jeffery Weir
Quickest Change Detection with Leave-one-out Density Estimation
In Proc. Proc. IEEE ICASSP, Rhodes, Greece, June 2023, May 2023 (Accepted)
Venu Veeravalli, Yuchen Liang
Adaptive Step-Size Methods for Compressed SGD
In Proc. Proc. IEEE ICASSP, Rhodes, Greece, June 2023., May 2023 (Accepted)
Venu Veeravalli, Akshayaa Magesh, Adarsh Subramaniam
Principled OOD Detection via Multiple Testing
In Proc. Proc. IEEE ISIT, Taipei, Taiwan, June 2023, May 2023 (Accepted)
Venu Veeravalli, Susmit Jha, Anirban Roy, Akshayaa Magesh
Robust High-Dimensional Linear Discriminant Analysis under Training Data Contamination
In Proc. Proc. IEEE ISIT, Taipei, Taiwan, June 2023, May 2023 (Accepted)
Venu Veeravalli, Aditya Deshmukh
Re-thinking computation offload for efficient inference on IoT devices with duty-cycled radios
In Proc. ACM Mobicom 2023, May 2023 (Accepted)
Deepak Ganesan , Jin Huang, Hui Guan
Acuity: Creating Realistic Digital Twins Through Multi-resolution Pointcloud Processing and Audiovisual Sensor Fusion
In Proc. The 8th ACM/IEEE Conference on Internet of Things Design and Implementation (IoTDI 2023), May 2023
Jason Wu, Ziqi Wang, Ankur Sarker, Mani Srivastava
Eagle: End-to-end Deep Reinforcement Learning based Autonomous Control of PTZ Cameras
In Proc. The 8th ACM/IEEE Conference on Internet of Things Design and Implementation (IoTDI 2023), May 2023
Sandeep Singh Sandha, Bharathan Balaji, Luis Garcia, Mani Srivastava
Performance Analysis of Deep-Learning Based Open Set Recognition Algorithms for Network Intrusion Detection Systems
In Proc. Proceedings of the 2023 IEEE/IFIP Network Operations and Management Symposium, May 2023
Gaspard Baye, Priscila Silva, Alexandre Broggi, Lance Fiondella, Nathaniel Bastian, Gokhan Kul
On-Demand Communication for Asynchronous Multi-Agent Bandits
In Proc. AISTATS 2023, May 2023
Yu-Zhen Janice Chen, Lin Yang, Xuchuang Wang, Xutong Liu, Mohammad Hajiesmali, John C.S. Lui, Don Towsley
Communication-efficient distributed learning: an overview
IEEE Journal on Selected Areas in Communication (JSAC), May 2023
Xuanyu Cao, Tamer Basar, Suhas Diggavi, Yonina Eldar, Khaled Letaief, Vincent Poor, Junshan Zhang
Inertial Navigation on Extremely Resource-Constrained Platforms: Methods, Opportunities and Challenges
In Proc. 2023 IEEE/ION Position, Location and Navigation Symposium (PLANS), April 2023
Swapnil Saha, Yayun Du, Sandeep Singh Sandha, Luis Garcia, Mohammad Khalid Jawed, Mani Srivastava
AcTrak: Controlling a Steerable Surveillance Camera using Reinforcement Learning
IEEE Transactions on Cyber-Physical Systems (IEEE TCPS), April 2023
Abdulrahman Fahim, Evangelos Papalexakis, Srikanth Krishnamurthy, Amit Chowdhury, Lance Kaplan, Tarek Abdelzaher
Scheduling IDK Classifiers with Arbitrary Dependences to Minimize the Expected Time to Successful Classification
Journal of Real-time Systems, March 2023
Tarek Abdelzaher, Kunal Agrawal, Sanjoy Baruah, Alan Burns, Robert Davis, Zhishan Guo, Yigong Hu
Delen: Enabling Flexible and Adaptive Model-serving for Multi-tenant Edge AI
In Proc. Proceedings of IEEE/ACM Eighth International Conference on Internet-of-Things Design and Implementation (IoTDI), February 2023 (Accepted)
Qianlin Liang, Walid Hanafy, Noman Bashir, David Irwin, Prashant Shenoy
Information Flow Optimization for Estimation in Linear Models Using a Sensor Network
IEEE Signal Processing Letters, February 2023 (Accepted)
Venu Veeravalli, Gunjan Verma, Aditya Deshmukh
Non-Parametric Quickest Mean-Change Detection
IEEE Transactions on Information Theory, February 2023
Venu Veeravalli, Yuchen Liang
Quickest Change Detection with Non-Stationary Post-Change Observations
IEEE Transactions on Information Theory, February 2023
Venu Veeravalli, Yuchen Liang
Robust Mean Estimation in High Dimensions: An Outlier- Fraction Agnostic and Efficient Algorithm
IEEE Transactions on Information Theory, February 2023 (Accepted)
Venu Veeravalli
Internet of Battlefield Things: Challenges, Opportunities, and Emerging Directions
IoT for Defense and National Security, Wiley, January 2023
Maggie Wigness, Tarek Abdelzaher, Stephen Russell, Ananthram Swami
The Methodological Pitfall of Dataset-Driven Research on Deep Learning: An IoT Example
In Proc. MILCOM, December 2022
Tianshi Wang, Denizhan Kara, Jinyang Li, Shengzhong Liu, Tarek Abdelzaher, Brian Jalaian
Decentralized Learning Robust to Data Poisoning Attacks
In Proc. IEEE Control and Decision Conference (CDC), December 2022
Yanwen Mao, Deepesh Data, Suhas Diggavi, Paulo Tabuada
GCNScheduler: Scheduling Distributed Computing Applications using Graph Convolutional Networks
In Proc. Proceedings of the 1st International Workshop on Graph Neural Networking, December 2022
Mehrdad Kiamari, Bhaskar Krishnamachari
Context-Aware Collaborative Neuro-Symbolic Inference in IoBTs
In Proc. MILCOM (IoT/AE), December 2022
Tarek Abdelzaher, Nathaniel Bastian, Susmit Jha, Lance Kaplan, Mani Srivastava, Venu Veeravalli
ControlVAE: Tuning, Analytical Properties, and Performance Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence, December 2022
Huajie Shao, Zhisheng Xiao, Shuochao Yao, Dachun Sun, Aston Zhang, Shengzhong Liu, Tianshi Wang, Jinyang Li, Tarek Abdelzaher
Graph Convolutional Network-based Scheduler for Distributing Computation in the Internet of Robotic Things
In Proc. IEEE MILCOM 2022, November 2022
Jared Coleman, Mehrdad Kiamari, Lillian Clark, Daniel D'Souza, Bhaskar Krishnamachari
AdaMask: Enabling Machine-Centric Video Streaming with Adaptive Frame Masking for DNN Inference Offloading
In Proc. ACM Multimedia, October 2022
Shengzhong Liu, Tianshi Wang, Jinyang Li, Dachun Sun, Mani Srivastava, Tarek Abdelzaher
Uncertainty Quantification using Query-Based Object Detectors
In Proc. ECCV Workshop on Uncertainty Quantification for Computer Vision, August 2022 (Accepted)
Meet Vadera, Colin Samplawski, Ben Marlin
Offline Policy Optimization with Eligible Actions
In Proc. Conference on Uncertainty in AI (UAI), August 2022
Yao Liu, Yannis Flet-Berliac
Proactive Resilience in 1-2-1 Networks
In Proc. 2022 IEEE International Symposium on Information Theory (ISIT), August 2022
Mine Dogan, Martina Cardone, Christina Fragouli
Multiple Testing Framework for Out-of-Distribution Detection
ArXiv, August 2022
Venu Veeravalli, Susmit Jha, Anirban Roy
Adaptive Step-Size Methods for Compressed SGD
Arxiv, August 2022
Venu Veeravalli
Quickest Change Detection with Controlled Sensing
In Proc. IEEE International Symposium on Information Theory (ISIT), August 2022
Venu Veeravalli
High-Dimensional Robust Mean Estimation via Outlier-Sparsity Minimization
In Proc. IEEE International Symposium on Information Theory (ISIT), August 2022
Venu Veeravalli
Comparison of Optimization Techniques for Risk, Deploy-Cost, and Makespan Aware Network Synthesis for Dispersed Computing
North American School of Information Theory (NASIT), August 2022
Jared Coleman, Eugenio Grippo, Bhaskar Krishnamachari
Real-Time Task Scheduling with Image Resizing for Criticality-based Machine Perception
Journal of Real-time Systems, August 2022
Yigong Hu, Shengzhong Liu, Tarek Abdelzaher, Maggie Wigness, Philip David
IoBT-OS: Optimizing the Sensing-to-Decision Pipeline for the Internet of Battlefield Things
In Proc. IEEE ICCCN , July 2022
Dongxin Liu, Tarek Abdelzaher, Tianshi Wang, Yigong Hu, Jinyang Li, Shengzhong Liu, Matt Caesar, Deepti Kalasapura, Joydeep Bhattacharyya, Nassy Srour, Maggie Wigness, Jae Kim, Guijun Wang, Greg Kimberly, Denis Osipychev, Shuochao Yao
DARTS: Distributed IoT Architecture for Real-Time, Resilient and AI-Compressed Workflows
In Proc. ACM ApPLIED (Advanced tools, programming languages, and PLatforms for Implementing and Evaluating algorithms for Distributed systems), Held in conjunction with PODC-2022, July 2022
Ragini Gupta, Bo Chen, Shengzhong Liu, Tianshi Wang, Tarek Abdelzaher, Klara Nahrstedt, Sandeep Singh Sandha, Mani Srivastava, Abel Souza, Prashant Shenoy, Jeffrey Smith, Maggie Wigness, Niranjan Suri
Machine Learning for Microcontroller-Class Hardware - A Review
IEEE Sensors Journal, July 2022
Swapnil Saha, Sandeep Sandha, Mani Srivastava
An Artificial Intelligence-Enabled Framework for Optimizing the Dynamic Cyber Vulnerability Management Process
In Proc. ICML 2022 Machine Learning for Cybersecurity Workshop, July 2022
Soumyadeep Hore, Ankit Shah, Nathaniel Bastian
Multi-View Scheduling of Onboard Live Video Analytics to Minimize Frame Processing Latency
In Proc. 42nd IEEE International Conference on Distributed Computing Systems (ICDCS), July 2022
Shengzhong Liu, Tianshi Wang, Hongpeng Guo, Xinzhe Fu, Philip David, Maggie Wigness, Archan Misra, Tarek Abdelzaher
Removing Batch Normalization Boosts Adversarial Training
In Proc. International Conference on Machine Learning (ICML), July 2022
Haotao Wang, Aston Zhang, Shuai Zheng, Xingjian Shi, Mu Li, Atlas Wang
TinyOdom: Hardware-Aware Efficient Neural Inertial Navigation
In Proc. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, July 2022
Swapnil Sayan Saha, Sandeep Singh Sandha, Luis Garcia, Mani Srivastava
AURITUS: An Open-Source Optimization Toolkit for Training and Deployment of Human Movement Models and Filters Using Earables
In Proc. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, July 2022
Swapnil Sayan Saha, Sandeep Singh Sandha, Siyou Pei, Vivek Jain, Ziqi Wang, Yuchen Li, Ankur Sarker, Mani Srivastava
Can We Break the Dependency in Distributed Detection?
In Proc. IEEE International Symposium on Information Theory, July 2022Hierarchical Learning Algorithms for Multi-scale Expert Problems
Proceedings of the ACM on Measurement and Analysis of Computing Systems, June 2022
Lin Yang, Yu-Zhen (Janice) Chen, Mohammad Hajiesmali, Mark Herbster, Don Towsley
Byzantine Fault-Tolerant Min-Max Optimization
Arxiv (arxiv.org), May 2022
Shuo Liu, Nitin Vaidya
Principal Manifold Flows
In Proc. 39th International Conference on Machine Learning (ICML), 2022, May 2022
Adam Cobb, Susmit Jha
Proactive Resilience in 1-2-1 Networks
In Proc. IEEE International Symposium on Information Theory, May 2022 (Accepted)
Mine Dogan, Martina Cardone, Christina Fragouli
Distributed adaptive Newton methods with global superlinear convergence
Automatica, May 2022
Jiaqi Zhang, Keyou You, Tamer Basar
A Minimax Learning Approach to Off-Policy Evaluation in Partially Observable Markov Decision Processes
In Proc. ICML-22, May 2022 (Accepted)
Chengchun Shi, Masatoshi Uehara, Jiawei Huang, Nan Jiang
Adversarially Trained Actor Critic for Offline Reinforcement Learning
In Proc. ICML-22, May 2022 (Accepted)
Ching-An Cheng, Tengyang Xie, Nan Jiang, Alekh Agarwal
Offline Reinforcement Learning Under Value and Density-Ratio Realizability: the Power of Gaps
In Proc. UAI-22, May 2022 (Accepted)
Jinglin Chen, Nan Jiang
Offline Reinforcement Learning with Realizability and Single-policy Concentrability
In Proc. COLT-22, May 2022 (Accepted)
Wenhao Zhan, Baihe Huang, Audrey Huang, Nan Jiang, Jason Lee
Self-Cueing Real-Time Attention Scheduling in Criticality-Driven Visual Machine Perception
In Proc. IEEE RTAS, May 2022
Shengzhong Liu, Xinzhe Fu, Maggie Wigness, Phil David, Shuochao Yao, Lui Sha, Tarek Abdelzaher
Building Robust Ensembles via Margin Boosting
In Proc. International Conference on Machine Learning (ICML), May 2022 (Accepted)
Pradeep Ravikumar
Distributed bandits with heterogeneous agents
In Proc. INFOCOM 2022, May 2022
Lin Yang, Yu-Zhen Chen, Mohammad Hajiesmali, John C.S. Lui, Don Towsley
Principles of Robust Learning and Inference for Internet of Battlefield Things
IoT for Defense and National Security, May 2022
Nathaniel Bastian, Susmit Jha, Paulo Tabuada, Venu Veeravalli, Gunjan Verma
Transfer Learning for Raw Network Traffic Detection
Expert Systems with Applications, May 2022
David Bierbrauer, Michael DeLucia, Krishna Reddy, Paul Maxwell, Nathaniel Bastian
Fairness Guarantees under Demographic Shift
In Proc. International Conference on Learning Representations, May 2022 (Accepted)
Philip Thomas
Fairness Guarantees under Demographic Shift
In Proc. International Conference on Learning Representations, May 2022
Philip Thomas
InkFiltration: Using Inkjet Printers for Acoustic Data Exfiltration From Air-Gapped Networks
ACM Transactions on Privacy and Security, May 2022
Julian de Gortari Briseno, Akash Singh, Mani Srivastava
Tracking the risk of a deployed model and detecting harmful distribution shifts
In Proc. International conference on learning representations, April 2022
Aleksandr Podkopaev, Aaditya Ramdas
Efficient Split-Mix Federated Learning for On-Demand and In-Situ Customization
In Proc. International Conference on Learning Representations (ICLR), April 2022
Junyuan Hong, Haotao Wang, Atlas Wang, Jiayu Zhou
Dual-Key Multimodal Backdoors for Visual Question Answering
In Proc. CVPR 2022, March 2022 (Accepted)
Susmit Jha
Runtime Monitoring of Deep Neural Networks Using Top-Down Context Models Inspired by Predictive Processing and Dual Process Theory
In Proc. Proceedings of the AAAI Spring 2022 Symposium on Designing Artificial Intelligence for Open Worlds, February 2022
Anirban Roy, Adam Cobb, Nathaniel Bastian, Brian Jalaian, Susmit Jha
Military and Security Applications: Cybersecurity
Encyclopedia of Optimization, February 2022
Nathaniel Bastian, Matthew Dinmore
Provably efficient reinforcement learning in decentralized general-sum Markov games
Journal of Dynamic Games and Applications, February 2022 (Accepted)
Weichao Mao, Tamer Basar
Convergence and optimality of policy gradient primal-dual method for constrained Markov decision processes
In Proc. 2022 American Control Conference, February 2022 (Accepted)
Dongsheng Ding, Kaiqing Zhang, Tamer Basar, Mihailo Jovanovic
Solving Multi-Arm Bandit Using a Few Bits of Communication
In Proc. AISTATS (International Conference on Artificial Intelligence and Statistics), January 2022 (Accepted)
Osama Hanna, Christina Fragouli, Lin Yang
Quickest Detection of Composite and Non-Stationary Changes with Application to Pandemic Monitoring
In Proc. IEEE ICASSP, January 2022
Venu Veeravalli, Yuchen Liang
Towards Deployment-Efficient Reinforcement Learning: Lower Bound and Optimality
In Proc. ICLR 2022, January 2022 (Accepted)
Jiawei Huang, Jinglin Chen, Li Zhao, Tao Qin, Nan Jiang, Tie-Yan Liu
URSABench: A System for Comprehensive Benchmarking of Bayesian Deep Neural Network Models and Inference methods
In Proc. Fifth Conference on Machine Learning and Systems, January 2022 (Accepted)
Meet Vadera, Jinyang Li, Adam Cobb, Brian Jalaian, Tarek Abdelzaher, Ben Marlin
Heavy-tailed Streaming Statistical Estimation
In Proc. International Conference on Artificial Intelligence and Statistics (AISTATS), January 2022 (Accepted)
Pradeep Ravikumar
An Online Learning Approach to Interpolation and Extrapolation in Domain Generalization
In Proc. International Conference on Artificial Intelligence and Statistics (AISTATS), January 2022 (Accepted)
Pradeep Ravikumar
On the Convergence Rate of Off-Policy Policy Optimization Methods with Density-Ratio Correction
In Proc. AISTATS 2022, January 2022 (Accepted)
Jiawei Huang, Nan Jiang
A System for Comprehensive Benchmarking of Bayesian Deep Neural Network Models and Inference methods
In Proc. Fifth Conference on Machine Learning and Systems , January 2022 (Accepted)
Meet Vadera, Jinyang Li, Tarek Abdelzaher, Ben Marlin
Robust Decision-Making in the Internet of Battlefield Things Using Bayesian Neural Networks
In Proc. Proceedings of the 2021 Winter Simulation Conference, December 2021
Adam Cobb, Brian Jalaian, Nathaniel Bastian, Stephen Russell
Evaluating Model Robustness to Adversarial Samples in Network Intrusion Detection
In Proc. Proceedings of the 2021 International Conference on Big Data, December 2021
Madeleine Schneider, David Aspinall, Nathaniel Bastian
Research Challenges for Combined Autonomy, AI, and Real-Time Assurance
In Proc. IEEE Int'l Conference on Cognitive Machine Intelligence (CogMI), December 2021
Tarek Abdelzaher, Sanjoy Baruah, Chris Gill, Eugene Voobeychik, Ning Zhang, Xuan Zhang
Enabling Hyperparameter Tuning of Machine Learning Classifiers in Production
In Proc. IEEE Conference on Cognitive Machine Intelligence (IEEE CogMI) , December 2021
Sandeep Sandha, Mohit Aggarwal, Swapnil Saha, Mani Srivastava
Competitive Algorithms for Online Multidimensional Knapsack Problems
Proceedings of the ACM on Measurement and Analysis of Computing Systems, December 2021
Lin Yang, Ali Zeynali, Mohammad Hajiesmali, Ramesh Sitaraman, Don Towsley
Detecting OODs as Datapoints with High Uncertainty
In Proc. Uncertainty & Robustness in Deep Learning Workshop @ ICML 2021, December 2021
Susmit Jha, Anirban Roy
Trinity: Trust, Resilience and Interpretability of Machine Learning Models
Game Theory and Machine Learning for Cyber Security (Wiley IEEE Press), December 2021
Susmit Jha, Brian Jalaian, Anirban Roy, Gunjan Verma
On Detection of Out of Distribution Inputs in Deep Neural Networks
In Proc. IEEE International Conference on Cognitive Machine Intelligence, December 2021 (Accepted)
Susmit Jha, Anirban Roy
iDECODe: In-distribution Equivariance for Conformal Out-of-distribution Detection
In Proc. AAAI 2022, December 2021 (Accepted)
Susmit Jha, Anirban Roy
AugMax: Adversarial Composition of Random Augmentations for Robust Training
In Proc. 35th Conference on Neural Information Processing Systems (NeurIPS 2021), December 2021
Haotao Wang, Chaowei Xiao, Jean Kossaifi, Zhiding Yu, Anima Anandkumar, Atlas Wang
Generating Realistic Cyber Data for Training and Evaluating Machine Learning Classifiers for Network Intrusion Detection Systems
Expert Systems with Applications, December 2021
Marc Chale, Nathaniel Bastian, Bruce Cox
Towards Safe Decision-Making via Uncertainty Quantification in Machine Learning
Systems Engineering and Artificial Intelligence (Springer), December 2021
Adam Cobb, Brian Jalaian, Nathaniel Bastian, Stephen Russell
Bayesian persuasion with state-dependent quadratic cost measures
IEEE Transactions on Automatic Control, March 2022, DOI: 10.1109/TAC.2021.3059679, December 2021 (Accepted)
Muhammed Sayin, Tamer Basar
Decentralized online convex optimization with feedback delay
IEEE Transactions on Automatic Control, June 2022, December 2021 (Accepted)
Xuanyu Cao, Tamer Basar
Finite-sample analysis for decentralized batch multi-agent reinforcement learning with networked agents
IEEE Transactions on Automatic Control, 66(12):5925-5940, 2021, DOI: 10.1109/TAC.2021.3049345, December 2021
Kaiqing Zhang, Zhuoran Yang, Han Liu, Tong Zhang, Tamer Basar
Distributed adaptive Newton methods with globally superlinear convergence
Automatica, 2022 (arXiv:2002.07378), December 2021 (Accepted)
Jiaqi Zhang, Keyou You, Tamer Basar
Derivative-free policy optimization for linear risk-sensitive and robust control design: Implicit regularization and sample complexity
In Proc. Proc. 35th Conference on Neural Information Processing Systems (NeurIPS 2021; December 6-14, 2021), Sydney, Australia, December 2021
Kaiqing Zhang, Xiangyuan Zhang, Bin Hu, Tamer Basar
Cooperative Stochastic Bandits with Asynchronous Agents and Constrained Feedback
In Proc. NEURIPS, December 2021
Lin Yang, Yu-Zhen Janice Chen, Stephen Pasteris, Mohammad Hajiesmali, John C.S. Lui, Don Towsley
Towards an Accurate Latency Model for Convolutional Neural Network Layers on GPUs
In Proc. MILCOM 2021, December 2021
Jinyang Li, Runyu Ma, Vikram Mailthody, Colin Samplawski, Ben Marlin, Songqing Chen, Shuochao Yao, Tarek Abdelzaher
Self-Contrastive Learning Based Semi-Supervised Radio Modulation Classification
In Proc. MILCOM 2021, December 2021
Dongxin Liu, Peng Wang, Tianshi Wang, Tarek Abdelzaher
Deep Contextualized Compressive Offloading for Images
In Proc. 3rd International Workshop on Challenges in Artificial Intelligence and Machine Learning for Internet of Things (AIChallengeIoT 21) , November 2021
Klara Nahrstedt, Prashant Shenoy, Bo Chen, Zhisheng Yan, Hongpeng Guo, Zhe Yang, Ahmed Ali-Eldin
LTE-based Pervasive Sensing Across Indoor and Outdoor
In Proc. ACM SenSys 2021, November 2021
Jie Xiong, Deepak Ganesan
Deep Contextualized Compressive Offloading for Images
AIChallengeIoT, Workshop co-located with ACM SenSys 2021, November 2021
Prashant Shenoy, Klara Nahrstedt, Bo Chen, Zhisheng Yan, Hongpeng Guo, Zhe Yang, Ahmed Ali-Elding
Portkey: Adaptive Key-Value Placement over Dynamic Edge Networks
In Proc. The ACM Symposium on Cloud Computing 2021 (ACM SoCC 2021), November 2021
Joseph Noor, Mani Srivastava, Ravi Netravali
COCOON - A Conductive Substrate-based Coupled Oscillator Network for Wireless Communication
In Proc. ACM SenSys 2021, November 2021
Deepak Ganesan
A Reinforcement Learning Approach for Scheduling in mmWave Networks
In Proc. MILCOM, November 2021 (Accepted)
Christina Fragouli, Mine Dogan
Network synthesis for tactical environments: scenario, challenges, and opportunities
In Proc. SPIE, November 2021 (Accepted)
Gunjan Verma, Christina Fragouli, Bhaskar Krishnamachari, Prashant Shenoy, Paulo Tabuada, Jonathan Burton, Mine Dogan, Jared Coleman, Eugenio Grippo, Abel Souza, Karl Olson, Matthew Maness
On the Computational Complexity of the Secure State-Reconstruction Problem
Automatica, November 2021 (Accepted)
Yanwen Mao, Aritra Mitra, Shreyas Sundaram, Paulo Tabuada
Decentralized Resilient State-Tracking
In Proc. 60th IEEE conference on Decision and Control, November 2021 (Accepted)
Yanwen Mao, Paulo Tabuada
Sequential Controlled Sensing for Composite Multihypothesis Testing
Sequential Analysis. 40(2): 259-289, May 2021, November 2021
Venu Veeravalli, Aditya Deshmukh, Srikrishna Bashyam
High-Dimensional Robust Mean Estimation via Outlier-Sparsity Minimization
In Proc. IEEE Asilomar Conference on Signals, Systems and Computers, Pacific Veeravalli-10 Grove, CA, November 2021, November 2021
Venu Veeravalli, Aditya Deshmukh, Jing Liu
Challenges and Opportunities in Approximate Bayesian Deep Learning for Intelligent IoT Systems
In Proc. Third IEEE International Conference on Cognitive Machine Intelligence, November 2021
Meet Vadera, Ben Marlin
Multi-Objective Network Synthesis for Dispersed Computing in Tactical Environments
In Proc. SPIE Signal Processing, Sensor/Information Fusion, and Target Recognition XXXI Conference, November 2021 (Accepted)
Jared Coleman, Eugenio Grippo, Bhaskar Krishnamachari, Gunjan Verma
RiLACS: Risk-Limiting Audits via Confidence Sequences
In Proc. Seventh International Joint Conference on Electronic Voting, November 2021 (Accepted)
Aaditya Ramdas
A unified framework for bandit multiple testing
In Proc. NeurIPS 2021, November 2021 (Accepted)
Aaditya Ramdas
QuPeD: Quantized Personalization via Distillation with Applications to Federated Learning
In Proc. Neural Information Processing Systems (NeurIPS) 2021, October 2021 (Accepted)
Kaan Ozkara, Navjot Singh, Deepesh Data, Suhas Diggavi
SQuARM-SGD: Communication-Efficient Momentum SGD for Decentralized Optimization.
IEEE Journal on Selected Areas in Information Theory, October 2021
Navjot Singh, Deepesh Data, Jemin George, Suhas Diggavi
Universal Off-Policy Evaluation
In Proc. NeurIPS 2021, October 2021 (Accepted)
Philip Thomas, Emma Brunskill, Bruno Castro da Silva, Erik Learned-Miller, Yash Chandak
Efficient and Resilient Edge Intelligence for the Internet of Battlefield Things
In Proc. NATO NATO STO IST Symposium on Artificial Intelligence, Machine Learning and Big Data, October 2021
Maggie Wigness, Tien Pham, Stephen Russell, Tarek Abdelzaher
Population Risk Improvement with Model Compression: An Information-Theoretic Approach
Entropy, Special Issue on Information Theory for Machine Learning, October 2021
Venu Veeravalli, Yuheng Bu, Shaofeng Zou, Weihao Gao
Policy Finetuning: Bridging Sample-Efficient Offline and Online Reinforcement Learning
In Proc. NeurIPS 2021, September 2021 (Accepted)
Tengyang Xie, Nan Jiang, Huan Wang, Caiming Xiong, Yu Bai
Bellman-consistent Pessimism for Offline Reinforcement Learning
In Proc. NeurIPS 2021, September 2021 (Accepted)
Tengyang Xie, Ching-An Cheng, Nan Jiang, Paul Mineiro, Alekh Agarwal
Towards Hyperparameter-free Policy Selection for Offline Reinforcement Learning
In Proc. NeurIPS 2021, September 2021 (Accepted)
Siyuan Zhang, Nan Jiang
Boosted CVaR Classification
In Proc. Neural Information Processing Systems (NeurIPS) 2021, September 2021
Pradeep Ravikumar
Audio Keyword Reconstruction from On-Device Motion Sensor Signals via Neural Frequency Unfolding
IMWUT, September 2021
Tianshi Wang, Shuochao Yao, Shengzhong Liu, Jinyang Li, Dongxin Liu, Huajie Shao, Ruijie Wang, Tarek Abdelzaher
Aerogel: Lightweight Access Control Framework for WebAssembly-Based Bare-Metal IoTNew publication
In Proc. The Sixth ACM/IEEE Symposium on Edge Computing (ACM SEC 2021), September 2021
Renju Liu, Luis Garcia, Mani Srivastava
Post-hoc loss-calibration for Bayesian neural networks
In Proc. Uncertainty in Artificial Intelligence, September 2021
Meet Vadera, Soumya Ghosh, Kenney Ng, Ben Marlin
Towards Transformer-Based Real-Time Object Detection at the Edge: A Benchmarking Study
In Proc. IEEE MILCOM, September 2021
Colin Samplawski, Ben Marlin
Optimizing Intelligent Edge-clouds with Partitioning, Compression and Speculative Inference
In Proc. IEEE MILCOM, September 2021
Shiwei Fang, Jin Huang, Colin Samplawski, Deepak Ganesan , Benjamin Marlin, Tarek Abdelzaher, Maggie Wigness, Ben Marlin
Real-Time Task Scheduling for Machine Perception in Intelligent Cyber-Physical Systems
IEEE Transactions on Computers, September 2021 (Accepted)
Shengzhong Liu, Shuochao Yao, Xinzhe Fu, Huajie Shao, Rohan Tabish, Simon Yu, Ayoosh Bansal, Heechul Yun, Lui Sha, Tarek Abdelzaher
Off-policy confidence sequences
In Proc. ICML 2021, August 2021 (Accepted)
Aaditya Ramdas
Incorporating the Measurement of Moral Foundations Theory in Analyzing Stances on Controversial Topics
In Proc. 32nd ACM Conference on Hypertext and Social Media (HT), August 2021
Rezvaneh Rezapour, Ly Dinh, Jana Diesner
Quantization of distributed data for learning
IEEE Journal on Selected Areas in Information Theory, August 2021 (Accepted)
Christina Fragouli, Suhas Diggavi, Osama Hanna, Yahya Ezzeldin
SQuARM-SGD: Communication-Efficient Momentum SGD for Decentralized Optimization
IEEE Journal on Selected Areas in Information Theory, August 2021 (Accepted)
Navjot Singh, Deepesh Data, Jemin George, Suhas Diggavi
Non-Parametric Quickest Detection of a Change in the Mean of an Observation Sequence
In Proc. CISS 2021, August 2021
Venu Veeravalli, Yuchen Liang
Quickest Change Detection in the Presence of Transient Adversarial Attacks
In Proc. CISS 2021, August 2021
Don Towsley, Venu Veeravalli, Thirupathaiah Vasantam
I Always Feel Like Somebody's Sensing Me! A Framework to Detect, Identify, and Localize Clandestine Wireless Sensors
In Proc. 30th USENIX Security Symposium, August 2021
Akash Singh, Luis Garcia, Joseph Noor, Mani Srivastava
On Exploring Image Resizing for Optimizing Criticality-based Machine Perception
In Proc. RTCSA , August 2021
Yigong Hu, Shengzhong Liu, Tarek Abdelzaher, Maggie Wigness, Phil David
Split to win: near-optimal sensor network synthesis via path-greedy subproblems
In Proc. Military Communications Conference (MILCOM), August 2021
Jonathan Bunton, Tzanis Anevlavis, Gunjan Verma, Christina Fragouli, Paulo Tabuada
Decentralized online convex optimization with feedback delays
IEEE Transactions on Automatic Control, June 2022, DOI: 10.1109/TAC.2021.3092562. , August 2021 (Accepted)
Xuanyu Cao, Tamer Basar
Semiparametric information state embedding for policy search under imperfect information
In Proc. Proceedings of the 60th IEEE Conference on Decision and Control (CDC'21, Dec 13-15, 2021; Austin, Texas), August 2021 (Accepted)
Sujay Bhatt, Weichao Mao, Alec Koppel, Tamer Basar
Cybersecurity Anomaly Detection in Adversarial Environments
In Proc. Proceedings of the AAAI Fall 2021 Symposium on AI in Government and Public Sector, August 2021
David Bierbrauer, Alexander Chang, Will Kritzer, Nathaniel Bastian
A Sensitivity Analysis of Poisoning and Evasion Attacks in Network Intrusion Detection Systems Machine Learning Models
In Proc. Proceedings of the 2021 Military Communications Conference, August 2021
Kevin Talty, John Stockdale, Nathaniel Bastian
Decentralized online convex optimization based on signs of relative states.
Automatica, 129:109676, July 2021, August 2021
Xuanyu Cao, Tamer Basar
Near-optimal model-free learning in non-stationary episodic MDPs
In Proc. International Conference on Machine Learning (ICML), PMLR 139, 2021. , August 2021
Weichao Mao, Kaiqing Zhang, Ruihao Zhu, David Simchi-Levi, Tamer Basar
Decentralized multi-agent reinforcement learning with networked agents: Recent advances.
Frontiers of Information Technology & Electronic Engineering, 22(6):802-814, 2021, August 2021
Kaiqing Zhang, Zhuoran Yang, Tamer Basar
Toward Uncertainty Aware Quickest Change Detection
In Proc. International Conference on Information Fusion, August 2021
James Hare, Lance Kaplan, Venu Veeravalli
On Proximal Policy Optimization's Heavy-tailed Gradients
In Proc. International Conference on Machine Learning (ICML), July 2021
Pradeep Ravikumar
Synthesis of Large-Scale Instant IoT Networks
IEEE Transactions on Mobile Computing, July 2021
Pradipta Ghosh, Jonathan Bunton, Dimitrios Pylorog, Marcos Vieira, Kevin Chan, Ramesh Govindan, Gaurav Sukhatme, Paulo Tabuada, Gunjan Verma
Nonstationary Reinforcement Learning with Linear Function Approximation
In Proc. Workshop on Reinforcement Learning Theory at ICML, July 2021
Huozhi Zhou, Jinglin Chen, Lav Varshney, Ashish Jagmohan
Contrastive Self-Supervised Representation Learning for Sensing Signals from the Time-Frequency Perspective
In Proc. ICCCN, July 2021
Dongxin Wang, Tianshi Wang, Shengzhong Liu, Ruijie Wang, Shuochao Yao, Tarek Abdelzaher
High Confidence Generalization for Reinforcement Learning
In Proc. ICML 2021, July 2021
Philip Thomas, James Kostas, Yash Chandak, Scott Jordan, Georgios Theocharous
Towards Practical Mean Bounds for Small Samples
In Proc. ICML 2021, July 2021
Philip Thomas, My Phan, Erik Learned-Miller
Batch Value-function Approximation with Only Realizability
In Proc. ICML 2021, July 2021
Xie Tengyang, Nan Jiang
Machine Learning/Artificial Intelligence for Sensor Data Fusion -- Opportunities and Challenges
IEEE Aerospace and Electronic Systems Magazine, July 2021
Eric Blasch, Tien Pham, Chee-Yee Chong, Wolfgang Koch, Henry Leung, Dave Braines, Tarek Abdelzaher
Semi-Supervised Contrastive Learning for Human Activity Recognition
In Proc. DCoSS, July 2021
Dongxin Liu, Tarek Abdelzaher
Adversarial Machine Learning in Network Intrusion Detection Systems
Expert Systems with Applications, July 2021
Paul Maxwell, Nathaniel Bastian, Elie Alhajjar
Adversarial Machine Learning in Network Intrusion Detection Systems
Expert Systems with Applications, July 2021
Elie Alhajjar, Paul Maxwell, Nathaniel Bastian
Deep Compressive Offloading: Speeding Up Edge Offloading for AI Services
GetMobile, June 2021
Shuochao Yao, Jinyang Li, Dongxin Liu, Tianshi Wang, Shengzhong Liu, Huajie Shao, Tarek Abdelzaher
Safety and stability guarantees for control loops with deep learning perception
IEEE Control Systems Letters (L-CSS), June 2021
Matteo Marchi, Jonathan Bunton, Bahman Gharesifard, Paulo Tabuada
Multi-Agent Reinforcement Learning: A Selective Overview of Theories and Algorithms
Handbook of Reinforcement Learning and Control, June 2021
Kaiqing Zhang, Zhuoran Yang, Tamer Basar
CrossRoI: Cross-camera Region of Interest Optimization for Efficient Real-Time Video Analytics at Scale
In Proc. ACM Multimedia Systems Conference (MMSys) 2021, June 2021
Hongpeng Guo, Klara Nahrstedt, Shuochao Yao, Zhe Yang, Qian Zhou
SVAD: End-to-End Sensory Data Analytics for IoBT-Driven Networks
In Proc. World Forum on Internet of Things (WF-IoT), 2021, June 2021
Ragini Gupta, Niranjan Suri, Jeffrey Smith, Klara Nahrstedt
SVAD: End-to-End Sensory Data Analytics for IoBT-Driven Networks
In Proc. World Forum on Internet of Things (WF-IoT), 2021, June 2021
Klara Nahrstedt, Niranjan Suri, Jeffrey Smith, Ragini Gupta
30th International Joint Conference on Artificial Intelligence (IJCAI), 2021
In Proc. 30th International Joint Conference on Artificial Intelligence (IJCAI), 2021, May 2021 (Accepted)
Sumit Jha, Rickard Ewetz, Alvaro Velasquez, Susmit Jha
Shaping Noise for Robust Attributions in Neural Stochastic Differential Equations
In Proc. AAAI 2022, May 2021 (Accepted)
Susmit Jha
Communication-efficient policy gradient methods for distributed reinforcement learning
IEEE Transactions on Control of Network Systems, 2022, DOI: 10.1109/TCNS.2021.3078100., May 2021 (Accepted)
Tianyi Chen, Kaiqing Zhang, Georgios Giannakis, Tamer Basar
Subseasonal Climate Prediction in the Western US using Bayesian Spatial Models
In Proc. Uncertainty in Artificial Intelligence (UAI), May 2021
Pradeep Ravikumar, Vishwak Srinivasan, Justin Khim, Arindam Banerjee
DORO: Distributional and Outlier Robust Optimization
In Proc. International Conference on Machine Learning (ICML), May 2021
Pradeep Ravikumar, Runtian Zhai, Chen Dan, Zico Kolter
Sequential (Quickest) Change Detection: Classical Results and New Directions
IEEE Journal on Selected Areas in Information Theory , April 2021
Liyan Xie, Shaofeng Zou, Yao Xie, Venu Veeravalli
Machine Learning for Raw Network Traffic Detection
In Proc. Proceedings of the 2021 SPIE Conference on Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications III, April 2021
Michael De Lucia, Paul Maxwell, Nathaniel Bastian, Ananthram Swami, Brian Jalaian, Nandi Leslie
Minimax Model Learning
In Proc. AISTATS 2021, April 2021
Cameron Voloshin, Nan Jiang, Yisong Yue
Distortion based Light-weight Security for Cyber-Physical Systems
IEEE Transactions on Automatic Control, April 2021
Gaurav Kumar Agarwal, Mohammed Karmoose, Suhas Diggavi, Christina Fragouli, Paulo Tabuada
Low-latency Speculative Inference On Distributed Multi-modal Data Streams
In Proc. 19th ACM International Conference on Mobile Systems, Applications, and Services (MobiSys 2021) , March 2021 (Accepted)
Deepak Ganesan , Tianxing Li, Jin Huang, Erik Risinger
Double Meta-Learning for Data Efficient Policy Optimization in Non-Stationary Environments
In Proc. ICRA, March 2021 (Accepted)
Elahe Aghapour, Nora Ayanian
SecDeep: Secure and Performant On-device Deep Learning Inference Framework for Mobile and IoT Devices
In Proc. ACM IoTDI 2021, March 2021
Renju Liu, Luis Garcia, Zaoxing Liu, Botong Ou, Mani Srivastava
Sim2Real Transfer for Deep Reinforcement Learning with Stochastic State Transition Delays
In Proc. The Conference on Robot Learning (CoRL) 2020, March 2021
Sandeep Sandha, Luis Garcia, Bharathan Balaji, Fatima Anwar, Mani Srivastava
Deep Convolutional Bidirectional LSTM for Complex Activity Recognition with Missing Data
In , March 2021
Swapnil Saha, Sandeep Sandha, Mani Srivastava
EScALation: A Framework for Efficient and Scalable Spatio-temporal Action Localization
In Proc. ACM Multimedia Systems Conference (MMSys) 2021, March 2021
Bo Chen, Klara Nahrstedt
Quickest Detection of Anomalies of Varying Location and Size in Sensor Networks
IEEE Transactions on Aerospace and Electronic Systems, Special Issue on Meta-level and Adversarial Tracking, 57(4): 2109 - 2120, August 2021, February 2021
Venu Veeravalli, Don Towsley, Ananthram Swami, George Rovatsos
Quickest Detection of Moving Anomalies in Sensor Networks
Journal on Selected Areas in Information Theory, Special Issue on Sequential Active and Reinforcement Learning, 2(2): 762-773, June 2021, February 2021
Venu Veeravalli, Georgios Rovatsos, George Moustakides
Joint Continuous and Discrete Model Selection via Submodularity
arXiv, February 2021
Jonathan Bunton, Paulo Tabuada
Decentralized policy gradient descent ascent for safe multi-agent reinforcement learning
In Proc. Proc. 35th AAAI Conference on Artificial Intelligence (AAAI-21, Feb 2-9, 2021; virtual), February 2021
Songtao Lu, Kaiqing Zhang, Tianyi Chen, Tamer Basar, Lior Horesh
High Confidence Off-Policy (or Counterfactual) Variance Estimation
In Proc. AAAI, February 2021
Philip Thomas, Yash Chandak, Shiv Shankar
SYMMETRIES AND ISOMORPHISMS FOR PRIVACY IN CONTROL OVER THE CLOUD
IEEE Transactions on Automatic Control, February 2021
Alimzhan Sultangazin, Paulo Tabuada
Sequential Algorithms for Moving Anomaly Detection in Networks
Sequential Analysis, Vol. 39, No. 1, 2020, January 2021
Georgios Rovatsos, Shaofeng Zou, Venu Veeravalli
Tightening Mutual Information Based Bounds on Generalization Error.
IEEE Journal on Selected Areas in Information Theory, January 2021
Yuheng Bu, Shaofeng Zou
Quickest Change Detection under Transient Dynamics: Theory and Asymptotic Analysis.
IEEE Transactions on Information Theory, January 2021
Shaofeng Zou, Georgios Fellouris
Y. Bu, S. Zou and V.V. Veeravalli
IEEE Journal on Selected Areas in Information Theory, 1(1): 121-130, May 2020, January 2021
Yuheng Bu, Shaofeng Zou
Tightening Mutual Information Based Bounds on Generalization Error.
IEEE Journal on Selected Areas in Information Theory, 1(1): 121-130, May 2020, January 2021
Yuheng Bu, Shaofeng Zou
Tightening Mutual Information Based Bounds on Generalization Error.
IEEE Journal on Selected Areas in Information Theory, 1(1): 121-130, May 2020., January 2021
Venu Veeravalli, Shaofeng Zou, Yuheng Bu
Quickest Change Detection under Transient Dynamics: Theory and Asymptotic Analysis.
IEEE Transactions on Information Theory, 65(3): 1397-1412, March 2019, January 2021
Venu Veeravalli, Shaofeng Zou, Georgios Fellouris
Quickest Detection of a Dynamic Anomaly in a Heterogeneous Sensor Network
In Proc. Proc. IEEE ISIT, Los Angeles, CA, June 2020., January 2021
Venu Veeravalli, George Rovatsos, George Moustakides
An Adversarial Training Based Machine Learning Approach to Malware Classification under Adversarial Conditions
In Proc. Proceedings of the 54th Hawaii International Conference on System Sciences, January 2021
Sean Devine, Nathaniel Bastian
SPARQ-SGD: Event-Triggered and Compressed Communication in Decentralized Optimization
In Proc. IEEE Control and Decision Conference (CDC) 2020, December 2020
Navjot Singh, Deepesh Data, Jemin George, Suhas Diggavi
To beam or not to beam? Beamforming with submodularity-inspired group sparsity
In Proc. 59th IEEE Conference on Decision and Control, December 2020
Tzanis Anevlavis, Jonathan Bunton, Anjaly Paril, Jemin George, Paulo Tabuada
Why not both? Exact continuous and discrete optimization with submodularity
In Proc. 59th IEEE Conference on Decision and Control, December 2020
Jonathan Bunton, Paulo Tabuada
Security Analysis of Safe and Seldonian Reinforcement Learning Algorithms
In Proc. NeurIPS 2020, December 2020
Philip Thomas, Pinar Ozisik
Towards Safe Policy Improvement for Non-Stationary MDPs.
In Proc. NeurIPS 2020, December 2020
Philip Thomas, Yash Chandak, Scott Jordan, Georgios Theocharous, Martha White
On Uncertainty and Robustness in Large-Scale Intelligent Data Fusion Systems
In Proc. CogMI 2020, December 2020
Ben Marlin, Tarek Abdelzaher, Gabriela Ciocarlie, Adam Cobb, Mark Dennison, Brian Jalaian, Lance Kaplan, Tiffany Raber, Adrienne Raglin, Piyush Sharma, Mani Srivastava, Theron Trout, Meet Vadera, Maggie Wigness
On Removing Algorithmic Priority Inversion from Mission-critical Machine Inference Pipelines
In Proc. IEEE Real-time Systems Symposium, December 2020
Shengzhong Liu, Shuochao Yao, Xinzhe Fu, Rohan Tabish, Simon Yu, Ayoosh Bansal, Heechul Yun, Lui Sha, Tarek Abdelzaher
Real-time Spatio-Temporal Action Localization in 360 Videos
In Proc. IEEE International Symposium on Multimedia (ISM 2020), December 2020
Bo Chen, Ahmed Ali-Eldin, Klara Nahrstedt, Prashant Shenoy
SEAWARE: Semantic-Aware View Prediction System for 360-degree Video Streaming
In Proc. IEEE International Symposium on Multimedia, December 2020
Klara Nahrstedt, Bo Chen, Jounsup Park, Mingyuan Wu, Eric Lee, Michael Zink, Ramesh Sitaraman
Real-time Spatio-Temporal Action Localization in 360 Videos
In Proc. IEEE International Symposium on Multimedia, December 2020
Klara Nahrstedt, Prashant Shenoy, Bo Chen, Ahmed Ali-Eldin
Security Analysis of Safe and Seldonian Reinforcement Learning Algorithms
In Proc. Advances in Neural Information Processing Systems, November 2020 (Accepted)UWHear: through-wall extraction and separation of audio vibrations using wireless signals
In Proc. ACM SenSys, November 2020
Ziqi Wang, Zhe Chen, Akash Deep Singh, Luis Garcia, Jun Luo, Mani Srivastava
Sim2Real Transfer for Deep Reinforcement Learning with Stochastic State Transition Delays
In Proc. Conference on Robot Learning (CoRL), November 2020
Sandeep Singh Sandha, Luis Garcia, Bharathan Balaji, Fatima Anwar, Mani Srivastava
Deep Compressive Offloading: Speeding Up Neural Network Inference by Trading Edge Computation for Network Latency
In Proc. 18th ACM Conference on Embedded Networked Sensor Systems (SenSys), November 2020
Shuochao Yao, Jinyang Li, Dongxin Liu, Tianshi Wang, Shengzhong Liu, Huajie Shao, Tarek Abdelzaher
Persuasion-based robust sensor design against attackers with unknown control objectives
IEEE Transactions on Automatic Control, 66(10):4589-4603, October 2021, DOI: 10.1109/TAC.2020.3030861, November 2020
Muhammed Sayin, Tamer Basar
Decentralized online convex optimization with event-triggered communications
IEEE Transactions on Signal Processing, 69:284-299, 2021 DOI: 10.1109/TSP.2020.3044843, November 2020
Xuanyu Cao, Tamer Basar
Model-based multi-agent RL in zero-sum Markov games with near-optimal sample complexity.
In Proc. Proc. 34th Conference on Neural Information Processing Systems (NeurIPS 2020, Dec 6-12, 2020), November 2020
Kaiqing Zhang, Sham Kakade, Tamer Basar, Lin Yang
Natural policy-gradient primal-dual method for constrained Markov decision processes
In Proc. Proc. 34th Conference on Neural Information Processing Systems (NeurIPS 2020, Dec 6-12, 2020), November 2020
Dongsheng Ding, Kaiqing Zhang, Tamer Basar, Mihailo Jovanovic
Robust multi-agent reinforcement learning with model uncertainty
In Proc. Proc. 34th Conference on Neural Information Processing Systems (NeurIPS 2020, Dec 6-12, 2020), November 2020
Kaiqing Zhang, Tao Sun, Yunzhe Tao, Sahika Genc, Sunil Mallya, Tamer Basar
POLY-HOOT: Monte-Carlo planning in continuous space MDPs with non-asymptotic analysis
In Proc. Proc. 34th Conference on Neural Information Processing Systems (NeurIPS 2020, Dec 6-12, 2020), November 2020
Weichao Mao, Kaiqing Zhang, Qiaomin Xie, Tamer Basar
An Improved analysis of (variance-reduced) policy gradient and natural policy gradient methods
In Proc. Proc. 34th Conference on Neural Information Processing Systems (NeurIPS 2020, Dec 6-12, 2020;), November 2020
Yanli Liu, Kaiqing Zhang, Tamer Basar, Wotao Yin
On the stability and convergence of robust adversarial reinforcement learning: a case study on linear quadratic systems
In Proc. Proc. 34th Conference on Neural Information Processing Systems (NeurIPS 2020, Dec 6-12, 2020), November 2020
Kaiqing Zhang, Bin Hu, Tamer Basar
SLATE: A Secure Lightweight Entity Authentication Hardware Primitive
IEEE Transactions on Information Forensics and Security, September 2020
Wei-Che Wang, Yair Yona, Yizhang Wu, Suhas Diggavi, Puneet Gupta
Qsparse-Local-SGD: Distributed SGD With Quantization, Sparsification, and Local Computations
IEEE Journal on Selected Areas in Information Theory (JSAIT), September 2020
Debraj Basu, Deepesh Data, Can Karakus, Suhas Diggavi
URSABench: Comprehensive Benchmarking of Approximate Bayesian Inference Methods for Deep Neural Networks.
In Proc. ICML Workshop on Uncertinaty in Deep Learning, September 2020
Ben Marlin, Brian Jalaian, Meet Vadera, Adam Cobb
Securing state reconstruction under sensor and actuator attacks: Theory and design
Automatica, September 2020
Mehrdad Showkatbakhsh, Yasser Shoukry, Suhas Diggavi, Paulo Tabuada
Handling Missing Sensors in Topology-aware IoT Applications with Gated Graph Neural Networks
Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT), September 2020 (Accepted)
Shengzhong Liu, Shuochao Yao, Yifei Huang, Dongxin Liu, Yiran Zhao, Jinyang Li, Tianshi Wang, Ruijie Wang, Chaoqi Yang, Tarek Abdelzaher
Deep Convolutional Bidirectional LSTM for Complex Activity Recognition with Missing Data
In Proc. International Conference on Activity and Behavior Computing (ABC2020), August 2020
Swapnil Saha, Sandeep Sandha, Mani Srivastava
Waiting Game: Optimally Provisioning Fixed Resources for Cloud-enabled Schedulers
In Proc. Proceedings of ACM/IEEE Conference on Supercomputing - SC20, August 2020 (Accepted)
Ambati Pradeep, Noman Bashir, David Irwin, Prashant Shenoy
Secure State-Reconstruction Over Networks Subject to Attacks
IEEE Control System Letters (joint publication also at cdc'20), August 2020
Yanwen Mao, Suhas Diggavi, Christina Fragouli, Paulo Tabuada
Finite-sample analysis for decentralized cooperative multi-agent reinforcement learning from batch data
In Proc. 21st IFAC World Congress (IFAC WC 2020), Berlin, Germany, July 12-17, 2020 (virtual), August 2020
Kaiqing Zhang, Zhuoran Yang, Han Liu, Tong Zhang, Tamer Basar
Global convergence of policy gradient methods to (almost) locally optimal policies
SIAM Journal on Control and Optimization, 58(6):3586-3612, 2020., August 2020
Kaiqing Zhang, Alec Koppel, Hao Zhu, Tamer Basar
Achieving globally superlinear convergence for distributed optimization with adaptive Newton method
In Proc. 59th IEEE Conference on Decision and Control (CDC'20, Dec 14-18, 2020; Jeju Island, Republic of Korea (virtual)), pp. 2329-2334. , August 2020
Jiaqi Zhang, Keyou You, Tamer Basar
Achieving globally superlinear convergence for distributed optimization with adaptive Newton method.
In Proc. . 59th IEEE Conference on Decision and Control (CDC'20, Dec 14-18, 2020; Jeju Island, Republic of Korea (virtual)), pp. 2329-2334., August 2020
Jiaqi Zhang, Keyou You, Tamer Basar
Approximate equilibrium computation for discrete-time linear-quadratic mean-field games
In Proc. Proc. 2020 American Control Conference (ACC 2020), Denver, Colorado, July 1-3, 2020 (virtual), pp. 333-339, August 2020
Muhammad Aneeq uz Zaman, Kaiqing Zhang, Erik Miehling, Tamer Basar
Reinforcement learning in non-stationary discrete-time linear-quadratic mean-field games
In Proc. 59th IEEE Conference on Decision and Control (CDC'20, Dec 14-18, 2020; Jeju Island, Republic of Korea (virtual)), pp. 2278-2284. , August 2020
Muhammad Aneeq uz Zaman, Kaiqing Zhang, Erik Miehling, Tamer Basar
Information state embedding in partially observable cooperative multi-agent reinforcement learning
In Proc. 59th IEEE Conference on Decision and Control (CDC'20, Dec 14-18, 2020; Jeju Island, Republic of Korea (virtual)), pp. 6124-6131. , August 2020
Weichao Mao, Kaiqing Zhang, Erik Miehling, Tamer Basar
Streisand games on complex social networks
In Proc. . 59th IEEE Conference on Decision and Control (CDC'20, Dec 14-18, 2020; Jeju Island, Republic of Korea (virtual)), pp. 1122-1127., August 2020
Sujay Bhatt, Tamer Basar
CAVE: Caching 360 Videos at the Edge
In Proc. ACM NOSSDAV 2022 , August 2020 (Accepted)
Ahmed Ali-Eldin, Mayank Jha, Chirag Goel, Bo Chen, Klara Nahrstedt, Prashant Shenoy
Scheduling Real-time Deep Learning Services as Imprecise Computations
In Proc. IEEE International Conference on Embedded and Real-time Computing Systems and Applications (RTCSA), August 2020
Shuochao Yao, Yifan Hao, Yiran Zhao, Huajie Shao, Dongxin Liu, Shengzhong Liu, Tianshi Wang, Jinyang Li, Tarek Abdelzaher
Differentially private parameter estimation: Optimal noise insertion and data owner selection
In Proc. 59th IEEE Conference on Decision and Control (CDC'20, Dec 14-18, 2020; Jeju Island, Republic of Korea (virtual)), pp. 2887-2893., August 2020
Xuanyu Cao, Tamer Basar
Decentralized multitask recursive least squares with local linear constraints
In Proc. 54th Asilomar Conference on Signals, Systems and Computers, Nov 1-4, 2020 (virtual), August 2020
Xuanyu Cao, Tamer Basar
Decentralized multi-agent stochastic optimization with pairwise constraints and quantized communications
IEEE Transactions on Signal Processing, 68:3296-3311, 2020 (published online: 29 May 2020. DOI: 10.1109/TSP.2020.2997394) , August 2020
Xuanyu Cao, Tamer Basar
Secure contingency prediction and response for cyber-physical systems
In Proc. IEEE Conference on Control Technology and Applications (CCTA), Montreal, Canada, August 24-26, 2020 (virtual), August 2020 (Accepted)
Erik Miehling, Cedric Langbort, Tamer Basar
Policy optimization for H-2 linear control with H-infinity robustness guarantee: implicit regularization and global convergence
In Proc. Proc. Machine Learning Research, 2020 (oral presentation at Conf Learning for Dynamics and Control (L4DC), University of California, Berkeley, CA, June 10-11, 2020 (virtual)), August 2020
Kaiqing Zhang, Bin Hu, Tamer Basar
AI on the Edge: Running AI-based IoT Applications Using Specialized Edge Architectures
In Proc. Proceedings of IEEE International Symposium on Workload Characterization, October 2020 , August 2020 (Accepted)
Qianlin Liang, David Irwin, Prashant Shenoy
AI on the Edge: Rethinking AI-based IoT Applications Using Specialized Edge Architectures
In Proc. Proceedings of IEEE International Symposium on Workload Characterization, October 2020, August 2020
Qianling Liang, David Irwin, Prashant Shenoy
New Frontiers in IoT: Networking, Systems, Reliability, and Security Challenges
IEEE IoT Journal, August 2020
Saurabh Bagchi, Tarek Abdelzaher, Ramesh Govindan, Prashant Shenoy, Ananksha Atrey, Pradipta Ghosh, Ran Xu
Byzantine Fault-Tolerant Distributed Machine Learning Using Stochastic Gradient Descent (SGD) and Norm-Based Comparative Gradient Elimination (CGE)
arXiv, August 2020
Nirupam Gupta, Shuo Liu, Nitin Vaidya
Misinformation Detection and Adversarial Attack Cost Analysis in Directional Social Networks
In Proc. 29th International Conference on Computer Communications and Networks (ICCCN), August 2020
Huajie Shao, Shuochao Yao, Andong Jing, Shengzhong Liu, Dongxin Liu, Tianshi Wang, Jinyang Li, Chaoqi Yang, Ruijie Wang, Tarek Abdelzaher
Truth Discovery with Multi-modal Data in Social Sensing
IEEE Transactions on Computers, August 2020 (Accepted)
Huajie Shao, Dachun Sun, Shuochao Yao, Lu Su, Zhibo Wang, Dongxin Liu, Shengzhong Liu, Lance Kaplan, Tarek Abdelzaher
Adversarial perturbations to manipulate the perception of power and influence in networks
6th International Conference on Computational Social Science, July 2020
Nikolaus Parulian, Tiffany Lu, Shubhanshu Mishra, Mihai Avram, Jana Diesner
Asynchronous Coagent Networks
In Proc. ICML 2020, July 2020
Philip Thomas, James Kostas, Chris Nota
ControlVAE: Controllable Variational Autoencoder
In Proc. Proc. International Conference on Machine Learning (ICML), July 2020
Huajie Shao, Shuochao Yao, Dachun Sun, Aston Zhang, Shengzhong Liu, Dongxin Liu, Jun Wang, Tarek Abdelzaher
CLIO: Enabling automatic compilation of deep learning pipelines across IoT and Cloud
In Proc. MOBICOM, July 2020
Jin Huang, Deepak Ganesan , Ben Marlin, Heesung Kwon
Multi-Agent Coordination for Distributed Transmit Beamforming
In Proc. 2020 American Control Conference, July 2020
Jemin George, Anjaly Parayil, Cemal Yilmaz, Bethany Allik, He Bai, Aranya Chakrabortty
Hierarchical Control of Multi-Agent Systems using\\ Online Reinforcement Learning
In Proc. 2020 American Control Conference, July 2020
Jemin George, He Bai, Aranya Chakrabortty
Boosting Cloud Data Analytics using Multi-Objective Optimization
In Proc. IEEE Intl Conference on Data Engineering (ICDE), 2021, July 2020 (Accepted)
Fei Song, Khaled Zaouk, Chenghao Lyu, Qi Fan, Yanlei Diao, Prashant Shenoy
Decentralized gradient methods: does topology matter?
In Proc. AISTATS 2020, June 2020
Giovanni Neglia, Chuan Xu, Don Towsley, Gianmarco Calbi
Effectiveness of the execution and prevention of metric-based adversarial attacks on social network data
Information, special issues on Social Influence, June 2020
Nikolaus Parulian, Tiffany Lu, Shubhanshu Mishra, Mihai Avram, Jana Diesner
Physics-based Simulation of Continuous-Wave LIDAR for Localization, Calibration and Tracking
In Proc. IEEE International Conference on Robotics and Automation, June 2020
Eric Heiden, Ziang Liu, Ragesh Ramachandran, Gaurav Sukhatme
Zero-Shot Learning in the Presence of Hierarchically Coarsened Labels
In Proc. 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) , May 2020
Colin Samplawski, Heesung Kwon, Erik Learned-Miller, Ben Marlin
Generalized Bayesian Posterior Expectation Distillation for Deep Neural Networks
In Proc. Conference on Uncertinaty in Artificial Intelligence, May 2020
Brian Jalaian, Ben Marlin, Meet Vadera
A Model-Free Approach to Distributed Transmit Beamforming
In Proc. 2020 ICASSP, May 2020
Jemin George, Cemal Yilmaz, Anjaly Parayil, Aranya Chakrabortty
Rapid Top-Down Synthesis of Large-Scale IoT Networks
In Proc. IEEE International Conference on Computer Communications and Networks (ICCCN 2020), May 2020
Pradipta Ghosh, Jonathan Bunton, Dimitrios Pylorof, Marcos Vieira, Kevin Chan, Ramesh Govindan, Gaurav Sukhatme, Paulo Tabuada, Gunjan Verma
Securing state reconstruction under sensor and actuator attacks: Theory and design
Automatica, May 2020
Mehrdad Showkatbakhsh, Yasser Shoukry, Suhas Diggavi, Paulo Tabuada
Fault-Tolerance in Distributed Optimization: The Case of Redundancy
In Proc. ACM Symposium on Principles of Distributed Computing, May 2020 (Accepted)
Nirupam Gupta, Nitin Vaidya
The Multi-domain Effects Loop: From Future Concepts to Research Challenges
In Proc. SPIE Defense and Commercial Sensing, April 2020
Tarek Abdelzaher, Adam Taliaferro, Paul Sullivan, Stephen Russell
Time Awareness in Deep Learning-Based Multimodal Fusion Across Smartphone Platforms
In Proc. Proceedins of the 5th ACM/IEEE Conference on Internet of Things Design and Implementation (IoTDI 2020), April 2020
Sandeep Sandha, Joseph Noor, Fatima Anwar, Mani Srivastava
Resilience in Collaborative Optimization: Redundant and Independent Cost Functions
arXiv, March 2020
Nirupam Gupta, Nitin Vaidya
GlobalFusion: A Global Attentional Deep Learning Framework for Multisensor Information Fusion
The Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT), March 2020
Shengzhing Liu, Shuochao Yao, Jinyang Li, Dobgxin Liu, Tianshi Wang, Huajie Shao
Adversarial perturbations to manipulate the perception of power and influence in networks
Women in Data Science Urbana-Champaign Conference 2020, March 2020
Tiffany Lu, Nikolaus Parulian, Mihai Avram, Shubhanshu Mishra, Jana Diesner
TrojDRL: Trojan Attacks on Deep Reinforcement Learning Agents
In Proc. 57th ACM/IEEE Design Automation Conference (DAC), 2020, March 2020
Panagiota (Penny) Kiourti, Kacper Wardega, Susmit Jha, Wenchao Li
Quickest Detection of Dynamic Events in Networks
IEEE Transactions on Information Theory, 66 (4): 2280-2295, April 2020, February 2020
Shaofeng Zou, Venu Veeravalli, Jian Li, Don Towsley
Information Flow Optimization in Inference Networks
In Proc. IEEE ICASSP 2020, February 2020
Aditya Deshmukh, Jing Liu, Venu Veeravalli, Gunjan Verma
Information-Theoretic Understanding of Population Risk Improvement with Model Compression
In Proc. AAAI 2020, February 2020
Yuheng Bu, Weihao Gao, Shaofeng Zou, Venu Veeravalli
Quickest Detection of Growing Anomalies in Networks
In Proc. IEEE ICASSP 2020, February 2020
Georgios Rovatsos, Venu Veeravalli, Don Towsley, Ananthram Swami
Analytical Modeling of Edge Clouds and its Applications
UMass Tech Report to be submitted to Sigmetrics 2021, February 2020
Ahmed Ali-Eldin, Y.C. Tay, Prashant Shenoy
Assessing the Adversarial Robustness of Monte Carlo and Distillation Methods for Deep Bayesian Neural Network Classification
AAAI SafeAI Workshop, February 2020
Meet Vadera, Satya Narayan Shukla, Brian Jalaian, Ben Marlin
Distributed Stochastic Gradient Descent with Event-Triggered Communication
In Proc. AAAI 2020, February 2020
Jemin George, Prudhvi Gurram
Five Challenges in Cloud-Enabled Intelligence and Control
ACM Transactions on Internet Technology, February 2020
Tarek Abdelzaher, Yifan Hao, Kasthuri Jayarajah, Archan Misra, Per Skarin, Shuochao Yao, Dulanga Weerakoon, Karl-Erik Arzen
Estimating the Density of States of Boolean Satisfiability Problems on Classical and Quantum Computing Platforms
In Proc. AAAI 2020 , January 2020
Tuhin Sahai, Anurag Mishra, Jose Miguel Pasini, Susmit Jha
On the Need for Topology-Aware Generative Models for Manifold-Based Defenses
In Proc. ICLR 2020, January 2020
Uyeong Wang, Susmit Jha, Somesh Jha
Cloud-scale VM Deflation for Running Interactive Applications On Transient Servers
In Proc. The 29th International Symposium on High-Performance Parallel and Distributed Computing , January 2020
Alex Fuerst, Ahmed Ali-Eldin, Prashant Shenoy, Prateek Sharma
Qsparse-Local-SGD: Distributed SGD With Quantization, Sparsification, and Local Computations
In Proc. Neural Information Processing Systems (NeurIPS) 2019, January 2020
Debraj Basu, Deepesh Data, Can Karakus, Suhas Diggavi
Adaptive Sequential Machine Learning
Sequential Analysis, Vol. 38, No. 4, 545 - 568, 2019, December 2019
Craig Wilson, Yuheng Bu, Venu Veeravalli
When is the Secure State-Reconstruction Problem Hard?
In Proc. IEEE Conference on Decision and Control, December 2019
Yanwen Mao, Aritra Mitra, Shreyas Sundaram, Paulo Tabuada
Attribution-Based Confidence Metric For Deep Neural Networks
In Proc. NeurIPS 2019, December 2019
Susmit Jha, Brian Jalaian, Gunjan Verma, Ananthram Swami
Symmetries and privacy in control over the cloud: uncertainty sets and side knowledge
In Proc. IEEE Conference on Decision and Control, December 2019
Alimzhan Sultangazin, Paulo Tabuada
Distributed Stochastic Gradient Method for Non-Convex Problems with Applications in Supervised Learning
In Proc. 2019 IEEE Conference on Decision and Control, December 2019
Jemin George, Tao Yang, He Bai, Prudhvi Gurram
Partially-observed discrete-time risk-sensitive mean-field games
In Proc. Proc. 58th IEEE Conference on Decision and Control (CDC'19, Dec 11-13, 2019; Nice, France), December 2019
Naci Saldi, Tamer Basar, Maxim Raginsky
A communication efficient multi-agent actor-critic algorithm for distributed reinforcement learning
In Proc. Proc. 58th IEEE Conference on Decision and Control (CDC19), Nice, France, December 11-13, 2019, December 2019
Yixuan Lin, Kaiqing Zhang, Zhuoran Yang, Zhaoran Wang, Tamer Basar, Romeil Sandhu, Ji Liu
Convergence and iteration complexity of policy gradient method for infinite-horizon reinforcement learning
In Proc. Proc. 58th IEEE Conference on Decision and Control (CDC'19); Nice, France; December 11-13, 2019., December 2019
Kaiqing Zhang, Alec Koppel, Hao Zhu, Tamer Basar
Secure linear quadratic regulator using sparse model-free reinforcement learning
In Proc. Proc. 58th IEEE Conference on Decision and Control (CDC19), Nice, France; December 11-13, 2019, December 2019
Bahare Kiumarsi, Tamer Basar
Non-cooperative inverse reinforcement learning
In Proc. Proc. 2019 Conference on Neural Information Processing Systems (NeurIPS'19, Dec 8-14, 2019; Vancouver, Canada), December 2019
Kaiqing Zhang, Xiangyuan Zhang, Erik Miehling, Tamer Basar
Policy optimization provably converges to Nash equilibria in zero-sum linear quadratic games
In Proc. Proc. 2019 Conference on Neural Information Processing Systems (NeurIPS'19, Dec 8-14, 2019; Vancouver, Canada), December 2019
Kaiqing Zhang, Zhuoran Yang, Tamer Basar
A Consensus-based Approach for Distributed Quickest Detection of Significant Events in Networks
In Proc. ASILOMAR 2019, December 2019
Jian Li, Don Towsley, Shaofeng Zou, Venu Veeravalli, Gabriela Ciocarlie
Active and Adaptive Sequential Learning with Per Time-step Excess Risk Guarantees
In Proc. Asilomar Conference on Signals Systems and Computers 2019, December 2019
Yuheng Bu, Jiaxun Lu, Venu Veeravalli
Quickest Detection of a Dynamic Anomaly in a Sensor Network
In Proc. Asilomar Conference on Signals Systems and Computers 2019, December 2019
Georgios Rovatsos, George Moustakides, Venu Veeravalli
TRINITY: Trust, Resilience and Interpretability of AI (Tutorial)
In Proc. Numerical Software Verification 2019 affiliated with CAV 2019, December 2019RemedIoT: Remedial Actions for Internet-of-Things Conflicts
In Proc. ACM BuildSys 2019, November 2019
Renju Liu, Ziqi Wang, Luis Garcia, Mani Srivastava
The Case for Robust Adaptation: Autonomic Resource Management is a Vulnerability
In Proc. IEEE MILCOM 2019 , November 2019
Joeseph Noor, Ahmed Ali-Eldin, Luis Garcia, Chirag Rao, Venkat Dasari, Deepak Ganesan , Brian Jalaian, Prashant Shenoy, Mani Srivastava
Pub/Sub-Sum: Content-summarization-based Pub/Sub Protocol on Information-centric Networks
In Proc. MILCOM 2019, November 2019
Jongdeog Lee, Suk Min Huang, Kelvin Marcus, Kavin Chan, Tarek Abdelzaher
Multi-Domain Effects and the Internet of Battlefield Things
In Proc. Milcom 2019, November 2019
Stephen Russell, Tarek Abdelzaher, Niranjan Suri
Application of Trust Assessment Techniques to IoBT Systems
In Proc. MILCOM 2019, November 2019
Ioannis Agadakos, Gabriela Ciocarlie, Bogdan Copos, Michael Emmi, Jemin George, Nandi Leslie, James Michaelis
On the optimality of linear signaling to deceive Kalman filters over finite/infinite horizons
In Proc. Proc. GameSec 2019 (10th International Conference on Decision and Game Theory for Security), October 30-November 1, 2019; Stockholm, Sweden., November 2019
Muhammed Sayin, Tamer Basar
Adversarial perturbations to manipulate the perception of power and influence in networks
iSchool Research Showcase 2019, October 2019
Mihai Avram, Shubhanshu Mishra, Nikolaus Parulian, Jana Diesner
Byzantine Fault-Tolerant Parallelized Stochastic Gradient Descent for Linear Regression
In Proc. 57th Annual Allerton Conference on Communication, Control, and Computing, September 2019
Nirupam Gupta, Nitin Vaidya
Sherlock - A Tool for Verification of Neural Network Feedback Systems: Demo Abstract.
In Proc. 22nd ACM International Conference on Hybrid Systems: Computation and Control (HSCC), 2019, September 2019TeLEx: learning signal temporal logic from positive examples using tightness metric
Formal Methods in System Design, September 2019
Susmit Jha
Hierarchical multi-stage Gaussian signaling games in noncooperative communication and control systems
Automatica (107:9-20, September 2019), August 2019
Muhammed Sayin, Emrah Akyol, Tamer Basar
Adversarial perturbations to manipulate the perception of power and influence in networks
In Proc. Workshop on Social Influence at the 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2019), August 2019
Mihai Avram, Shubhanshu Mishra, Nikolaus Parulian, Jana Diesner
Scheduling Shared Data Acquisition for Real-time Decision Making
In Proc. RTCSA , August 2019
Tai-Sheng Cheng, Tarek Abdelzaher
Data Encoding Methods for Byzantine-Resilient Distributed Optimization
In Proc. IEEE International Symposium on Information Theory, July 2019
Deepesh Data, Linqi Song, Suhas Diggavi
Byzantine-Tolerant Distributed Coordinate Descent
In Proc. IEEE International Symposium on Information Theory, July 2019
Deepesh Data, Suhas Diggavi
Data Encoding for Byzantine-Resilient Distributed Gradient Descent
In Proc. IEEE International Symposium on Information Theory (ISIT), July 2019
Deepesh Data, Linqi Song, Suhas Diggavi
Online planning for decentralized stochastic control with partial history sharing
In Proc. Proc. 2019 American Control Conference (ACC 2019), Philadelphia, Pennsylvania, July 10-12, 2019, July 2019
Tamer Basar, Kaiqing Zhang, Erik Miehling
Quickest Detection of a Moving Target in a Sensor Network
In Proc. IEEE ISIT 2019, July 2019
Georgios Rovatsos, Shaofeng Zou, Venu Veeravalli
Evolution of Cooperation in Network of Interacting Agents
In Proc. 2019 American Control Conference, July 2019
Jemin George, Ananthram Swami
Fast Distributed Least-Squares Solver for Linear Time-Varying Equations
In Proc. 2019 American Control Conference, July 2019
Jemin George, Tao Yang
Assessing the Robustness of Bayesian Dark Knowledge to Posterior Uncertainty
ICML 2019 Workshop on Uncertainty & Robustness in Deep Learning, July 2019
Meet Vadera, Ben Marlin
Distributed Learning over Time-Varying Graphs with Adversarial Agents
In Proc. 2nd International Conference on Information Fusion, Special Session on Internet of Battlefield Things, July 2019
Pooja Vyavahare, Lili Su, Nitin Vaidya
Eugene: Towards Deep Intelligence as a Service
In Proc. ICDCS 2019, July 2019
Shuochao Yao, Tarek Abdelzaher
The Price is (Not) Right: Reflections on Pricing for Transient Cloud Servers
In Proc. Proceedings of IEEE ICCCN Valencia, Spain, July 2019, July 2019
David Irwin, Prashant Shenoy, Pradeep Ambati, Prateek Sharma, Supreeth Shastri, Ahmed Ali-Eldin
Tightening Mutual Information Based Generalization Bounds
In Proc. IEEE ISIT 2019, July 2019
Yuheng Bu, Shaofeng Zou, Venu Veeravalli
SpotWeb: Running Latency-sensitive Distributed Web Services on Transient Cloud Server
In Proc. The 28th International Symposium on High-Performance Parallel and Distributed Computing , June 2019
Ahmed Ali-Eldin, Jonathan Westin, Bin Wang, Prateek Sharma, Prashant Shenoy
Adversarial perturbations for identifying strategies toward biasing the perceptions of power and influence in social networks
In Proc. SUNBELT 2019 - Social Networks Conference of the International Network for Social Network Analysis (INSNA), June 2019
Mihai Avram, Shubhanshu Mishra, Parulian Nikolaus, Jana Diesner
Enhancing the measurement of social effects by capturing morality
In Proc. 10th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis (WASSA) co-located at the North American Chapter of the Association for Computational Linguistics (NAACL), June 2019
Rezvaneh Rezapour, Saumil Shah, Jana Diesner
Understanding the Synchronization Costs of Distributed Machine Learning on Transient Cloud Resources
In Proc. Proceedings of IEEE Intl Cloud Engg Conference , June 2019
Prashant Shenoy, Ahmed Ali-Eldin, David Irwin, Pradeep Ambati, Lixin Gao
Game Theory for Next Generation Wireless and Communication Networks: Modeling, Analysis, and Design.
Cambridge University Press, June 2019
Zhu Han, Dusit Niyato, Walid Saad, Tamer Basar
Model Change Detection with Application to Machine Learning
In Proc. IEEE ICASSP 2019, May 2019
Yuheng Bu, Jiaxun Lu, Venu Veeravalli
Distributed Quickest Detection of Significant Events in Networks
In Proc. ICASSP 2019, May 2019
Jian Li, Venu Veeravalli, Don Towsley, Ananthram Swami, Shaofeng Zou
SpyCon: Adaptation Based Spyware in Human-in-the-Loop IoT
In Proc. SafeThings 2019: IEEE Workshop on the Internet of Safe Things, May 2019
Salma Elmalaki, Bo-Jhang Ho, Moustafa Alzantot, Yasser Shoukry, Mani Srivastava
Inferring Private Information in Wireless Sensor Networks
In Proc. 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), May 2019
Daniel Burbano, Jemin George, Randy Freeman, Kevin Lynch
DISTRIBUTED TRACKING OF MANEUVERING TARGET: A FINITE-TIME ALGORITHM
In Proc. 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), May 2019
Jemin George
Attribution-driven Causal Analysis for Detection of Adversarial Examples
In Proc. SafeML workshop at ICLR 2019, May 2019
Susmit Jha, Brian Jalaian, Ananthram Swami, Gunjan Verma
STFNets: Learning Sensing Signals from the Time-Frequency Perspective with Short-Time Fourier Neural Networks
In Proc. The Web Conference (WWW), May 2019
Shuochao Yao, Ailing Piao, Wenjun Jiang, Yiran Zhao, Huajie Shao, Shengzhong Liu, Dongxin Liu, Jinyang Li, Tianshi Wang, Shaohan Hu, Lu Su, Jiawei Han, Tarek Abdelzaher
A Semi-Supervised Active-learning Truth Estimator for Social Networks
In Proc. The Web Conference (WWW), May 2019
Hang Cui, Tarek Abdelzaher, Lance Kaplan
The Role of Network Topology for Distributed Machine Learning
In Proc. INFOCOM 2019, April 2019
Giovanni Neglia, Gianmarco Calbi, Don Towsley, Gayane Vardoyan
Enhancing the measurement of social effects by capturing morality
iSchool Corporate Research Showcase, April 2019
Rezvaneh Rezapour, Saumil Shah, Jana Diesner
The Age of Social Sensing
IEEE Computer, April 2019
Dong Wang, Boleslaw Szymanski, Tarek Abdelzaher, Heng Ji, Lance Kaplan
Evrostos: The rLTL Verifier
In Proc. International Conference on Hybrid Systems: Computation and Control, April 2019
Matthew Philippe, Daniel Neider, Paulo Tabuada, Tzanis Anevlavis
Demo Abstract: DDFlow Visualized Declarative Programming for Heterogeneous IoT Networks on Heliot Testbed Platform
The 4th ACM/IEEE International Conference on Internet of Things Design and Implementation (IoTDI '19 Posters and Demos), April 2019
Joseph Noor, Sandeep Singh Sandha, Luis Garcia, Mani Srivastava
Dependable Machine Intelligence at the Tactical Edge
In Proc. SPIE Defense and Commercial Sensing, April 2019
Archan Misra, Kasthuri Jayarajah, Dulanga Weekaroon, Shuochao Yao, Tarek Abdelzaher
Towards an Intelligent Tactical Edge: An Internet of Battlefield Things Roadmap
In Proc. SPIE Defense and Commercial Sensing, April 2019
Tarek Abdelzaher, Stephen Russell
DDFlow: Visualized Declarative Programming for Heterogeneous IoT Networks
In Proc. ACM/IEEE International Conference on Internet of Things Design and Implementation (IoTDI), April 2019
Joseph Noor, Hsiao-Yun Tseng, Luis Garcia, Mani Srivastava
Byzantine Fault Tolerant Distributed Linear Regression
arXiv.org, April 2019
Nirupam Gupta, Nitin Vaidya
Sherlock : A Tool for Verification of Deep Neural Networks.
In Proc. AAAI Spring Symposium on Verification of Neural Networks (VNN), 2019., February 2019
Susmit Jha
Inferring and Conveying Intentionality: Beyond Numerical Rewards to Logical Intentions.
In Proc. AAAI Spring Symposium, Towards Conscious AI Systems, 2019, February 2019
Susmit Jha
Tightening Mutual Information Based Bounds on Generalization Error
ISIT, 2019, February 2019A Risk-Sensitive Finite-Time Reachability Approach for Safety of Stochastic Dynamic Systems
In Proc. ACC, 2019, February 2019
Susmit Jha
Securing Smart Cities: Implications and Challenges
Book, February 2019 (Accepted)
Ioannis Agadakos, Prashant Anantharaman, Gabriela Ciocarlie, Bogdan Copos, Michael Emmi, Tancrede Lepoint, Ulf Lindqvist, Michael Locasto, Liwei Song
Distributed Learning with Adversarial Agents Under Relaxed Network Condition
Arxiv.org, February 2019
Pooja Vyavahare, Nitin Vaidya
Robust Dynamic Average Consensus Algorithms
IEEE Transactions on Automatic Control, February 2019 (Accepted)
Jemin George, Randy Freeman
Communication scheduling and remote estimation with adversarial intervention
IEEE/CAA Journal of Automatica Sinica, 6(1): 32-44, January 2019., February 2019
Tamer Basar, Xiaobin Gao, Emrah Akyol
Security for Resilient IoBT Systems: Emerging Research Directions
In Proc. The First International Workshop on Internet of Things for Adversarial Environments, January 2019
Ioannis Agadakos, Gabriela Ciocarlie, Bogdan Copos, Jemin George, Nandi Lesli, James Michaelis
Human-in-the-loop control of distributed multi-agent systems: A relative input-output approach
In Proc. Proceedings of the 2018 IEEE Conference on Decision and Control (CDC 2018), pp. 3343-3348, Miami, FL, December 17-19, 2018, December 2018
Tamer Basar, Bahare Kiumarsi
Towards the use of symmetries to ensure privacy in control over the cloud
In Proc. IEEE Conference on Decision and Control, December 2018
Alimzhan Sultangazin, Paulo Tabuada
Verifying rLTL formulas: now faster than ever before
In Proc. IEEE Conference on Decision and Control, December 2018
Tzanis Anevlavis, Matthew Philippe, Daniel Neider, Paulo Tabuada
On communication scheduling and remote estimation in the presence of an adversary as a non-zero-sum game
In Proc. 2018 IEEE Conference on Decision and Control (CDC 2018), pp. 2710-2715, Miami, FL, December 2018., December 2018
Tamer Basar, Xiaobin Gao, Emrah Akyol
Learning Task Specifications from Demonstrations.
In Proc. NIPS 2018, December 2018
Susmit Jha, Sanjit Seshia
Deep Learning for the Internet of Battlefield Things
NATO SET-262 Specialists' Meeting on Artificial Intelligence for Military Multisensor Fusion Engines, November 2018
Tarek Abdelzaher
FastDeepIoT: Towards Understanding and Optimizing Neural Network Execution Time on Mobile and Embedded Devices
In Proc. ACM Sensys , November 2018
Shuochao Yao, Yiran Zhao, Huajie Shao, Shengzhong Liu, Dongxin Liu, Lu Su, Tarek Abdelzaher
Towards an Internet of Battlefield Things: A Resilience Perspective
IEEE Computer, November 2018
Tarek Abdelzaher, Nora Ayanian , Tamer Basar, Suhas Diggavi, Jana Diesner, Deepak Ganesan , Ramesh Govindan, Susmit Jha, Tancrede Lepoint, Ben Marlin, Klara Nahrstedt, David Nicol, Raj Rajkumar , Stephen Russell, Sanjit Seshia, Fei Sha, Prashant Shenoy, Mani Srivastava, Gaurav Sukhatme, Ananthram Swami, Paulo Tabuada, Don Towsley, Nitin Vaidya, Venu Veeravalli
Quickest Detection of Significant Events in Structured Networks
In Proc. Asilomar Conference on Signals, Systems, and Computers 2018, November 2018
Shaofeng Zou, Venu Veeravalli, Jian Li, Don Towsley
Distributed aggregative games on graphs in adversarial environments
In Proc. Proc. GameSec 2018 (9th International Conference on Decision and Game Theory for Security), October 29-31, 2018; Seattle, WA, pp. 296-313. , October 2018
Tamer Basar, Bahare Kiumarsi
Bias Mitigation of Morality Measurement through Quality-Controlled Lexicon Expansion and Evaluation
iSchool Research Showcase, October 2018
Rezvaneh Rezapour, Saumil Shah, Jana Diesner
Adversarial perturbations for identifying strategies for biasing the perceptions of power and influence in social networks
iSchool Research Showcase, October 2018
Mihai Avram, Shubhanshu Mishra, Jana Diesner
Detecting Adversarial Examples Using Data Manifolds
In Proc. MILCOM 2018, October 2018
Susmit Jha, Brian Jalaian
On Tracking Realistic Targets in a Megacity with Contested Air and Spectrum Access
In Proc. MILCOM, October 2018
Jongdeog Lee, Tarek Abdelzaher, Hang Qiu, Ramesh Govindan, Kelvin Marcus, Reginald Hobbs, Niranjan Suri, Will Dron
The Internet of Battlefield Things: The Next Generation of C3I
In Proc. MILCOM, October 2018
Stephen Russell, Tarek Abdelzaher
Executing Analytics and Fusion Workloads on Transient Computing Resources in Tactical Environments'
In Proc. IEEE MILCOM 2018, October 2018
Ahmed Ali-ElDin, Deepak Ganesan , Heesung Kwon, Ben Marlin, Prashant Shenoy, Mani Srivastava, Don Towsley
Internet of Personalized and Autonomous Things (IoPAT)
In Proc. ACM International Workshop on Smart Cities and Fog Computing (CitiFog '18) , October 2018
Salma Elmalaki, Yasser Shoukry, Mani Srivastava
Generating Dominant Strategies for Continuous Two-Player Zero-Sum Games
In Proc. IFAC Conference on Analysis and Design of Hybrid Systems (ADHS), October 2018
Sanjit Seshia
Data-Efficient Learning of Robust Control Policies
In Proc. Allerton Control Conference, October 2018
Susmit Jha, Patrick Lincoln
Towards the use of symmetries to ensure privacy in control over the cloud
In Proc. 57th IEEE Conference on Decision and Control (CDC 2018), October 2018
Paulo Tabuada, Alimzhan Sultangazin
Distorting an Adversary's View in Cyber-Physical Systems
In Proc. 57th IEEE Conference on Decision and Control (CDC 2018) , October 2018
Gaurav Agarwal,, Mohammed Karmoose, Suhas Diggavi, Christina Fragouli, Paulo Tabuada
Verifying rLTL formulas: now faster than ever before!
In Proc. 57th IEEE Conference on Decision and Control (CDC 2018), October 2018
Tzanis Anevlavis, Matthew Philippe, Daniel Neider, Paulo Tabuada
VirtSense: Virtualize Sensing through ARM TrustZone on Internet-of-Things
In Proc. 3rd Workshop on System Software for Trusted Execution (SysTEX 2018), October 2018
Renju Liu, Mani Srivastava
Intelligent Robotic IoT System (IRIS) Testbed
In Proc. IEEE/RSJ International Conference on Intelligent Robots and Systems, October 2018
Jason A. Tran, Pradipta Ghosh, Yutong Gu, Richard Kim, Daniel D'Souza, Nora Ayanian , Bhaskar Krishnamachari
SenseGAN: Enabling Deep Learning for Internet of Things with a Semi-Supervised Framework
IMWUT (Formerly Ubicomp), September 2018
Shuochao Yao, Yiran Zhao, Huajie Shao, Chao Zhang, Aston Zhang, Shaohan Hu, Dongxin Liu, Shengzhong Liu, Lu Su, Tarek Abdelzaher
Polymorphic radios: A new design paradigm for ultra-low power communication
In Proc. SIGCOMM 2018, August 2018
Deepak Ganesan , Mohammad Rostami
Protecting the privacy of networked multi-agent systems controlled over the cloud
In Proc. 27th International Conference on Computer Communications and Networks (ICCCN 2018), July 2018
Alimzhan Sultangazin, Suhas Diggavi, Paulo Tabuada
QuickSketch: Building 3D Representations in Unknown Environments using Crowdsourcing
In Proc. Fusion 2018, July 2018
Fawad Ahmad, Hang Qiu, Fan Bai, Ramesh Govindan
Risks and Benefits of Side-Channels in Battlefields
In Proc. Fusion 2018, July 2018
Tancrede Lepoint, Ioannis Agadakos, Bogdan Copos, Gabriela Ciocarlie, Michael Locasto, Ulf Lindqvist, James Michaelis
A Command-by-Intent Architecture for Battlefield Information Acquisition Systems
In Proc. Fusion 2018, July 2018
Jongdeog Lee, Yifan Hao, Tarek Abdelzaher, Kelvin Marcus, Reginald Hobbs
ApDeepSense: Deep Learning Uncertainty Estimation Without the Pain for IoT Applications
In Proc. In Proc. IEEE International Conference on Distibuted Computing Systems (ICDCS), July 2018
Shuochao Yao, Yiran Zhao, Huajie Shao, Chao Zhang, Aston Zhang, Dongxin Liu, Shengzhong Liu, Lu Su, Tarek Abdelzaher
Trusted Neural Networks for Safety-Constrained Autonomous Control
In Proc. DISE1: Deep Learning for Safety-Critical Applications in Engineering co-located with ICML, AAMAS and IJCAI, 2018, July 2018
Susmit Jha
Will Distributed Computing Revolutionize Peace? The Emergence of Battlefield IoT
In Proc. ICDCS 2018, July 2018
Tarek Abdelzaher, Nora Ayanian , Tamer Basar, Suhas Diggavi, Jana Diesner, Deepak Ganesan , Ramesh Govindan, Susmit Jha, Tancrede Lepoint, Ben Marlin, Klara Nahrstedt, David Nicol, Raj Rajkumar , Stephen Russell, Sanjit Seshia, Fei Sha, Prashant Shenoy, Mani Srivastava, Gaurav Sukhatme, Ananthram Swami, Paulo Tabuada, Don Towsley, Nitin Vaidya, Venu Veeravalli
Generalized Colonel Blotto game
In Proc. Proc. 2018 American Control Conference (ACC 2018), Milwaukee, WI, June 27-29, 2018, pp. 5744-5749, June 2018
Tamer Basar, Anibal Sanjab, Walid Saad, Aidin Ferdowsi
Duality-Based Nested Controller Synthesis from STL Specifications for Stochastic Linear Systems
In Proc. 16th International Conference on Formal Modeling and Analysis of Timed Systems (FORMATS), June 2018
Susmit Jha, Sunny Raj, Sumit Jha, Natarajan Shankar
Privacy-Utility Trade-off of Linear Regression under Random Projections and Additive Noise
In Proc. IEEE International Symposium on Information Theory, June 2018
Suhas Diggavi, Mehrdad Showkatbaksh, Can Karakus
Model, Data and Reward Repair: Trusted Machine Learning for Markov Decision Processes
In Proc. Proceedings of the DSN Workshop on Dependable and Secure Machine Learning (DSN-DSML), co-located with the IEEE/IFIP International Conference on Dependable Systems and Networks, June 2018
Susmit Jha
A Constrained Maximum Likelihood Estimator for Unguided Social Sensing
In Proc. IEEE International Conference on Computer Communications (IEEE Infocom), June 2018
Huajie Shao, Shuochao Yao, Yiran Zhao, Chao Zhang, Jinda Han, Lance Kaplan, Lu Su, Tarek Abdelzaher
Verifying Controllers Against Adversarial Examples with Bayesian Optimization
In Proc. International Conference on Robotics and Automation (ICRA'18), May 2018
Shromona Ghosh
Deep Learning for the Internet of Things
IEEE Computer, May 2018
Shuochao Yao, Yiran Zhao, Aston Zhaon, Shaohan Hu, Huajie Shao, Chao Zhang, Lu Su, Tarek Abdelzaher
Quickest Detection of Dynamic Events in Sensor Networks
In Proc. Proc. IEEE ICASSP 2018, April 2018
Shaofeng Zou, Venu Veeravalli
Output Range Analysis for Deep Neural Networks
In Proc. Tenth NASA Formal Methods Symposium (NFM 2018), April 2018
Souradeep Dutta, Susmit Jha
Learning and Verification of Feedback Control Systems using Feedforward Neural Networks
In Proc. IFAC Conference on Analysis and Design of Hybrid Systems (ADHS18), April 2018
Souradeep Dutta, Susmit Jha
Realizing the full potential of (infra-)structures for inter-agency communication before, during, and after disasters using the example of APAN (All-Partners Access Network)
In Proc. The 3rd International Workshop on Social Sensing (SocialSens 2018), April 2018
Ly Dinh, Jana Diesner
Athena: Towards Decision-centric Anticipatory Sensor Information Delivery
Journal of Sensor and Actuator Networks, January 2018
Jongdeog Lee, Kelvin Marcus, Tarek Abdelzaher, Tanvir Amin, Will Dron, Ramesh Govindan, Reginald Hobbs, Shaohan Hu, Amotz Bar-Noy, Jung-Eun Kim, Shuochao Yao
RDeepSense: Reliable Deep Mobile Computing Models with Uncertainty Estimation
ACM IMWUT (formerly UbiComp), December 2017
Shuochao Yao, Yiran Zhao, Huajie Shao, Aston Zhang, Chao Zhang, Shen Li, Tarek Abdelzaher